Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: Novel technology, such as (VR), can offer greater accessibility and can be delivered remotely, cost-effectively and conveniently without transportation and provide individually tailored treatments (Su et al. 2021; Thielbar et al. 2020). In the clinical setting, several trials have innovated and investigated effective treatments for ULMI recovery. They have identified VR technology as an opportunity to promote movement recovery during the physiotherapeutic process (Levac et al. 2013). VR-supported rehabilitation has a high intrinsic motivational power that increases engagement and enjoyment of therapeutic routines for adults and children (Campo-Prieto et al. 2021; Chen et al. 2014; Laver et al. 2017). This is very important because even if a proper rehabilitation therapy is prescribed, and it can fail because of the patient’s lack of motivation (López-Jaquero et al. 2019; Meyns et al. 2018). In addition, it is effective in reducing procedural pain, with minimal adverse effects and economical due to the reduced costs of the technology (Aydın and Özyazıcıoğlu 2019; Chan et al. 2020; Chen et al. 2020, Garrett et al. 2014; Walther-Larsen et al. 2019). It lets users immerse themselves in an engaging and challenging virtual scenario where interaction emulates the exercises required in their CR (Wenk et al. 2021). It also allows therapists to identify individuals’ difficulties and customise the control of variables, such as speed, size, distance and visual and auditory feedback (Brusque et al. 2018; Zahabi et al. 2020). The “Impact VRLab” based in Sheffield has developed a suite of immersive and interactive VR rehabilitation systems for paediatric and adult patients with neurological and musculoskeletal conditions, orthopaedic trauma, and pain management (Chau et al. 2020; Furness et al. 2019; Phelan et al. 2019). Immersive scenarios possessing high degrees of the patient presence and engagement proved the most effective (Furness et al. 2019). A small scale feasibility study was carried out to help children with ULMI to perform their rehabilitation exercises in a clinical setting. Results showed a reduction in pain and difficulty ratings, increased enjoyment and improved range of motion (ROM). [SEP] Justify:

Output: The text corroborates the claim by discussing the use of VR technology in physical therapy to promote movement recovery. It mentions that VR-supported rehabilitation increases engagement, enjoyment, and motivation for patients during their therapy sessions, which aligns with the claim about using VR for guided exercises to help regain mobility. The text also references clinical settings where VR has been effectively utilized to facilitate rehabilitation exercises, thereby providing further evidence supporting the claim.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: The authors work in [16] used transfer learning classifiers that recognize the social media language indicative of mental health outcomes for studying the changes in psycho-social expressions over language and time during Covid-19. The proposed model can study not only the linguistic changes but also the temporal changes in combination with support expressions. The authors [2] used techniques like conversation models that are sequence-based, language model comparisons, message clustering, to present a set of computational discourse analysis algorithms for calculating the relationship between various linguistic features of conversations and conversation outcomes. The novel methods developed are suited for datasets that are large-scale and can be used to discover actionable conversation strategies associated with better conversational outcomes. However, with only a small set of linguistic features, the model performs well [1]. The work proposed in [19] used Network to replicate relationship between the user and the community they interact in. Then, discussion trees were analysed, extracting descriptors that unwrap the discussed main topic. The model detects what the main messages of the set of comments are, and also gives a description of what is being discussed in different communities. This can let counsellors skip irrelevant parts and help the person in need. The work in [11] proposed a technique which used regression machine learning models on multiple tweets and compared with outcomes of Software to score tweets on a perceived anxiety scale. The model can help in determining the anxiety levels of a person based on their multiple tweets with very small error. The work authors in [3] used Machine learning models to classify short comments into positive and negative data using character level analysis to find precision, and accuracy of the model. It is predicted that classifying with a short statement uttered daily will lead to early identification of mental problems. However, the accuracy of classification can be bettered by using words’ vector representation that includes their meaning. The work proposed in [7] employed logistic regression framework to distinguish between those who have suicide intent vs. those who have shifted from a mental illness state to suicide state. This study established a method that tells if a person engaged in mental health discussions is prone to shift to suicidal ideation. Previous works (Table 1) include classification of mental health status of users using Machine and Network, where the column for performance attainment corresponds to the accuracy to the models proposed. Many models and architectures have been developed in order to create more accurate systems. [SEP] Justify:

Output: The text contrasts the claim by discussing various models and methods used in analyzing language, particularly in the context of mental health outcomes. Although it highlights advancements in understanding emotional tone within social media and mental health contexts, it indicates that the systems have limitations, such as the need for a small set of linguistic features and potential inaccuracies in classification. Therefore, these limitations suggest that translation AI tools do not perfectly interpret emotional tone and intention.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: Figures AbstractIn the Colombian context, disputes over natural resources, mainly over land, and poor governance are intertwined with armed conflict. Although efforts to address this situation, including the 2016 peace agreement signed between Colombian government and the Forces of Colombia (FARC, by Spanish acronym) are underway, these disputes continue, affecting land use dynamics. Understanding the complexity and trends in land use conflicts, as well as the specific regional characteristics underlying differing land use changes across regions, is critical. This 9088. Vadrevu, University of Maryland at : September 24, 2021; Accepted: May 14, 2022; Published: May 31, 2022Copyright: © 2022 Del Río Duque et al. This is an open access 2016. Other authors state that forests that were previously inaccessible are now open to land grabbing, in particular with conversion to cattle pastures as a result of land speculation and land accumulation [18, 19]. However, according to Negret et al. [23], this tendency depends on regional features such as local governance. Against this background, the current situation of land use conflicts poses a critical challenge in the Colombian post-agreement context. To understand land use changes in conflict-affected territories in Colombia, a systematic exploration of the complex land use dynamics is required. Few authors map this complexity using causal loop diagrams (CLDs). For example, the study of Rocha et al. [28] uses CLDs to understand land use changes in across different cases. They recognize that CLDs allow for reconciling common regional drivers with context-dependent features. Furthermore, Molina et al. [29] develop CLDs to improve the systemic understanding of factors affecting sustainability in the agro-ecosystems of the páramos in Colombia. This tool allows them to integrate different elements and feedbacks of these agro-ecosystems, thus broadening discussions about future effects and expected behaviors. Another highly insightful study is that of Arias-Gaviria et al. [30]. The scholars analyze deforestation in Colombia using the conceptual framework of socio-ecological systems and CLDs as a tool for mapping interactions between different sub-systems and agents. This study contributes to a better understanding of the complexity of deforestation, a key issue related to land use dynamics in Colombia. Since the complexity of land use changes is determined by regional patterns [31], it is important to expand its study to regional research that considers context-dependent features. [SEP] Justify:

Output: The text focuses on land use conflicts and governance issues in Colombia, with no mention or implication of nature sounds or their effects on peace and productivity. Therefore, it is irrelevant to the claim regarding the impact of nature sounds.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: The objective measurement scales were captured using a goniometer measurement instrument to capture ROM (Phelan et al. 2021a, b). This study aims to explore the feasibility, acceptability and perceived effectiveness of an overhauled Reality (IVR) system tailored for ULMI rehabilitation for children in their homes. Using feedback acquired through co-design with patients, caregivers and clinical staff, a new improved system specifically tailored for home use was developed. Selected outcome measures include ROM readings, quality of life (PedsQL), usability (SUS) and qualitative data (interviews). The redesign of the system builds on previous studies by incorporating additional immersive levels with new mechanics (arrow types) that replicate physiotherapy exercises (stretching, flexions and rotations). Usability required significant attention since the user would be using the system in their homes without instant support. This required the inclusion of a character that follows the user to provide tips on how to progress. Motivational challenges and engaging scenarios were implemented to maintain the users’ attention to prevent the therapy from failing, as is often the case with self-directed treatments. An aim of this study is to provide rehabilitation to paediatric patients with ULMI to optimise functional outcomes and overall well-being and quality of life. Utilising IVR technology with self-directed home rehabilitation, this system attempts to decrease healthcare pressure due to the Covid-19 pandemic by reducing clinic visits. This alternative approach to rehabilitation at home does not require supervised sessions. Although the therapist still needs to perform an initial assessment along with training on how to use the system, the subsequent follow-up appointments should be reduced with the improvement in adherence. 2 Related workVR scenarios can be presented through a head-mounted device (IVR), or a projection system or a flat-screen (non-IVR). The state of the art of clinical studies conducted to demonstrate the efficacy and acceptability of VR for ULMI rehabilitation has been primarily focussed on adults and non-immersive VR systems. There is a lack of clinical studies of IVR applied to children and in particular during home-based rehabilitation. 2. 1 Non-IVR interventionNon-IVR environments provide visual feedback, presented through projection systems or flat screens. Biofeedback enables control of the timing of the task and supports motor learning (Kitago and Krakauer 2013). [SEP] Justify:

Output: The text corroborates the claim by discussing the use of an improved immersive virtual reality (IVR) system designed for rehabilitation, specifically tailored to patients with upper limb motor impairment (ULMI). It highlights that the system replicates physiotherapy exercises, such as stretching and rotations, which aligns with the concept of using guided exercises in physical therapy to help patients regain mobility.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: Architectures like DistilBERT aim at creating compact version of these technologies in order to improve their ability to be deployed at network edges. This forms a solid groundwork for applying the sentiment analysis methods in prediction models to create a more robust system where classification of emotions can be extended to analysis the influence of various factors and model predictions based on it. Table 1 Table of related workFull size tableThe proposed architecture aims at solving the following gaps: 1. The existing approaches refined and classified the data based on a score value to predict the mental state, using methods such as Machines, Logistic Regression, and [6, 8, 18]. This is in contrast to the approach followed in this paper, which is forecasting social interactions effect as a regression-based task. 2. There exists a scope of studying the continuously changing emotional tone in online mental illness group interactions in order to predict their effects. This work aims at creating such a prediction model by modelling the user’s mental state during his/her interaction in a sequence of comments to forecast shifts in their emotional tone, to get a more accurate result. Analysis of the shift in the mental state of author after each comment is explored, and the determination of final mental state of author in relation to final comment is predicted. 3 Shifts modelling in emotional tone3. 1 Polarity and subjectivity of commentsThe TextBlob library is an open-source python Processing (NLP) tool which can perform sentiment analysis on test using lexicon-based approach. It takes the input text and generate two values one for polarity and one for subjectivity of the text. This gives us the sentiment type i. e. , positive or negative sentiment behind a comment. It also gives us the level of objectivity in a sentence and hence provides the degree of personal opinions and emotions involved in a particular comment. Thus, nature of the comments in a subreddit can be analyzed in terms of these two factors. Exploring these factors gives us an idea about the prevalent emotional state and temperament of comments in these subreddits, which can be correlated to the effect of interactions on the post author. We also specifically focus on the polarity of the last comments in all threads to see the final emotional status of the author. 3. 2 Emotional toneIn a particular publication, that can be either a post or a document, the emotional intensity or tone is measured by a sentiment analysis tool called VADER. [SEP] Justify:

Output: The text contrasts the claim by discussing the limitations and challenges of existing language model architectures in interpreting emotional tone and intent. It highlights that while there are efforts to enhance sentiment analysis through tools like TextBlob and VADER, the complexities of accurately forecasting shifts in emotional tone during interactions remain a subject of ongoing research. Furthermore, it explicitly states that the ability to analyze emotional tone is still developing and is not universally perfected in translation AI tools.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: To this end, the paper addresses two main questions: (1) what are the systemic land use dynamics in two strategic and contrasting case studies: Cesar and Caquetá, and (2) how can systemic innovation address land use conflicts? Our paper contributes to the existing literature by analyzing land use dynamics under a complex system approach that comprehensively maps the interactions and feedbacks related to land use changes. Through a case study comparison and using causal loop diagrams (CLDs) our paper sheds light on the land use dynamics in these two study regions. These CDLs also contribute to a better understanding of the interrelation between three subcomponents of the system: environmental, social, and economic [30, 32–34]. Case study backgroundColombia is located on the northwestern end of at latitude 4°06’56. 42" N and longitude of 72°55’48. 49"W. Colombia comprises 32 departments and the of Bogotá. Departments are subdivided into municipalities. The departments, in turn, can be grouped into six very distinct natural regions: Caribbean, Andean, Pacific, Orinoquía, Amazon, and Insular. We selected two conflict-affected departments of Colombia as case studies: one located in the Amazon region, Caquetá. This region covers 132,218 km2, or 11. 6% of the country’s surface. The other, Cesar, is located in the Caribbean region. This region covers 403,348 km2, or 35. 3% of the country´s surface (Fig 1). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 1. Study regions: Departments of Cesar and Caquetá. Elaborated by authors. America map obtained from GADM (free available at: and the Agricultural frontier of Cesar and Caquetá shape obtained from Unidad de Planificación Rural Agropecuaria–UPRA (free available at: The data contained in the table was taken from the following official sources in Colombia:. located in the southern region, is the third largest department in Colombia with an area equivalent to 7. 8% of the national territory, has an important role at national level due to its unique biological corridors and great variety of fauna and flora: it is considered to be one of the most mega-biodiverse departments in the country [35]. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the systemic land use dynamics in Colombia and does not mention anything about nature sounds or their potential effects on environment or productivity. The focus is entirely on land use conflicts and the geographical aspects of two specific Colombian regions.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: The most frequently used devices are computer-based supported, such as -Fit (Kong et al. 2016; Simonsen et al. 2017). 2. 1. 1 Intervention with adult patients: upper limb stroke impairmentsThe majority studies have been with adults with a focus on stroke patients. The randomised controlled trial (RCT) of Kiper et al. (2018) with stroke patients demonstrated the effectiveness of reinforced feedback in non-IVR treatment, combined with CR for upper limb and compared with just CR. Similarly, Lee et al. (2018) investigated the effects of game-based non-IVR canoe paddling training, when combined with CR programs, on postural balance and upper limb function in stroke patients (n = 30). Results showed significant improvements compared with the baseline measurements and significantly greater improvement in the experimental group compared with the control group (p < 0. 05). Shahmoradi et al. (2021) presented a single before–after study to evaluate the impact of the non-IVR games on UL rehabilitation in chronic stroke patients (n = 10; mean age 52). The games had positive effects on the shoulder abduction (16. 26 ± 23. 94, p < 0. 02), adduction (59. 24 ± 74. 76, p < 0. 00), wrist supination (0. 06 ± 1. 34, p < 0. 03). As one of the first studies to evaluate the use of VR for ULMI rehabilitation after stroke, combining non-IVR and home-based approaches, Piron et al. (2009) compared a remotely controlled programme to treat motor deficits in post-stroke patients (n = 36) with CR. The experimental treatment was a non-IVR virtual reality-based system delivered via the Internet, which provided motor tasks to the patients from a remote rehabilitation facility with the therapist’s support. Results showed the Fugl-(FMA-UE) indicated a significantly higher improvement in post-treatment motor function in the experimental group. Based on self-directed therapy, a different approach was presented by Wittman et al. (2016), who conducted an open-label, single-group study with stroke patients (n = 11). The patients trained with an inertial measurement unit (IMU)-based non-IVR system (ArmeoSenso) in their homes for six weeks. [SEP] Justify:

Output: The text corroborates the claim by providing evidence that virtual reality (VR) has been utilized in upper limb rehabilitation for stroke patients, indicating its positive impact on motor function and rehabilitation. Specifically, the reference to Piron et al. (2009) mentions a virtual reality-based system designed for post-stroke patients that involved delivering motor tasks remotely, which aligns with the claim of VR being used to help patients regain mobility through guided exercises.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: From experimentation, we observe a positive higher value obtained of the emotional tone, which suggests that the supportive comments made by other users have helped the author to feel better as a result. The average emotional tone generally pans out to be positive, as supportive comments are offered to the author, thus resulting in a positive value for the emotional tone. Overall, the results display the fact that being a part of respective mental illness groups, the familiar environment provides empathy and support for each other, thus making an improvement in one’s emotional being. 5 Experimental setupThe execution and performance analysis of the proposed model was conducted using software. The core algorithm was developed using Python and compiled using Python 3. 3. 2. The experiments were conducted using a HP PC consisting of an Intel® Core™ i7-7300HQ 2. 50 GHz CPU in a 64-bit Windows-10 OS. To obtain the predictions of emotional tone, from the sequence of data extracted from different subreddits, we use RNN as it performs well with sequential data. We have used RNN using Units (GRUs), as GRUs help making a decision as to what information is to be passed on to the output as compared to a standard RNN. Since we’re finding the prediction of emotional tone in a numeric form, implying a regression task, the hidden layer of RNN (half of Ym) is passed through a (FC) layer to get the scalar prediction y for EmT(cn). If a unidirectional RNN is used, hidden state of the last comment in sequence T is used, whereas a bi-directional RNN, the final hidden states are joined i. e. the forward and backward halves of the network. Loss function Since this is a regression task, mean squared error (MSE Loss) and mean absolute error (L1 loss) are generally used as loss functions but with training using these, the model was unable to gather predictions along the average, thus preventing from accurate predictions of further extreme values of emotional tone EmT(cn). Hence, we use Weighted L1 loss because the distribution of emotional tone y varies between − 1 and 1, forming a bell curve [4]. We weight the absolute error for (X, y) proportionally to the reciprocal of the number of elements in its bin. 10 equal-length bins are used [10]. [SEP] Justify:

Output: The text contrasts the claim by detailing how RNNs are utilized for predicting emotional tone but also highlights their limitations. Specifically, it mentions that 'the model was unable to gather predictions along the average, thus preventing from accurate predictions of further extreme values of emotional tone EmT(cn).' This indicates that while the AI can capture some aspects of emotional tone, it does not do so perfectly, undermining the claim of perfect interpretation.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: As this department is dominated by the Amazonian rainforest, land-based production activities are constrained. In this sense, 63. 4% of its area is natural protected area and 20. 5% are natural forest and non-agricultural areas [36]. However, historically Caquetá was integrated into the country through successive processes of colonization since the mid-nineteenth century, a process that stimulated the non-vocational use of the land and prioritized extractivism [37]. Further, since its geographical location was suitable, the Forces of Colombia (FARC) established its military activities there, thus making the armed conflict a long-standing central factor in its socio-spatial configuration. Not only was the department the scene of two failed peace negotiations during the governments of (1982–1986) and Andrés Pastrana (1999–2002), it also witnessed the largest state attempt to defeat the FARC within the policy of the government of Álvaro Uribe (2002–2010). Neither the State nor the FARC ever completely controlled Caquetá. Rather, State action has lagged behind the colonization process, has failed to order the territory, and has been completely substituted by the FARC in some areas [38]. However, the new peace process changed the dynamics within the region, as we explore in this study. In contrast, Cesar, located in the northern region, is ranked 21 of 33 according to its area (2% of the national territory) and is 95% rural. Despite its small size, it has four strategic ecosystems for conservation: de Santa Marta, Serranía del Perijá, the valley of the and the valley of the Magdalena River. has lost around 90% of Forest (TDF)–only 720,000 of 8. 8 million hectares estimated remain–Cesar region has the largest volume of TDF remnants in the country, at 72,401 ha, or 21. 8% [39]. According to Instituto Geográfico Agustín Codazzi [40], both productivity and conservation could be combined in the department because of its 2. 2 million hectares: 48% is suitable for different types of production and 51. 2% should be protected due to its environmental importance. Palm oil crops, coal mining, cocoa, and livestock are the main economic activities in the region. Coal mining is particularly causing environmentaland social damages. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses the socio-political and environmental context of regions in Colombia, particularly around land use and conflict, without mentioning the effects of nature sounds on peace or productivity.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: Comparisons between LMCBT and CR groups showed similar results in all parameters in all disease groups (p > 0. 05). Thus, this study has quantitatively shown that LMCBT should be an effective alternative treatment option in children and adolescents with physical disabilities. On the other hand, Choi et al. (2021) carried out an RCT to investigate the efficacy of a non-IVR rehabilitation system of wearable multi-inertial sensors to improve arm function in children with brain injury (n = 80). Results showed a significant improvement in upper limb dexterity functions (Assessment of Limb Function-2 (MA-2)), after treatment, significantly higher in the experimental group (DELTA = 10. 09 ± 10. 50) compare with the control group (DELTA = 3. 65 ± 6. 92) (p < 0. 05). Although the results found by these studies are relevant and demonstrate positive results, suggesting that non-IVR can help in the rehabilitation of children with ULMI, more research is needed for a broader range of clinical conditions and with systems with greater capacity for immersion and interaction. 2. 2 IVR rehabilitationIVR environments are presented to the patients through a HMD, and this technology increases the user’s level of immersion (presence) in the environment. This plays an essential role in providing an optimal condition for task practice, as does the meaning of the task for the user (Kitago and Krakauer 2013; Martirosov et al. 2021). In the literature, we found studies in which IVR was used to improve UL rehabilitation. This mainly focussed on stroke and CP injuries, where paediatric upper limb injuries require a task-specific physiotherapeutic approach different from injuries and burns (Bortone et al. 2020; Mekbib et al. 2020, 2021). Interestingly, only one study was conducted with the paediatric population. Mekbib et al. (2020) designed and then, implemented a neuroscience-based IVR protocol to rehabilitate stroke adult patients. The system provides unilateral and bilateral limb reflex exercises in a fully immersive virtual environment that can stimulate and activate the mirror neuron system in the brain to assist rehabilitation in subacute stroke patients (n = 12). Following the intervention, the primary outcome was that patients demonstrated a significant improvement in their motor function FMA-UE scores (p < 0. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of immersive virtual reality (IVR) environments in rehabilitation. It highlights that IVR can enhance a user's immersion, thereby providing optimal conditions for task practice, which is essential in physical therapy. Additionally, the text mentions studies that utilized IVR for improving upper limb function, particularly in stroke and cerebral palsy patients, supporting the idea that virtual reality is effectively integrated into physical therapy regimens to aid in mobility recovery.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: of sentences for each subreddit: anxiety, bipolar, suicidewatch and depressionFull size imageThe figures in the second row under each subreddit shows the magnitude of polarity vs. the number of sentences for all the comments in a particular subreddit. From the figure it is evident that the polarity value of comments is a good mix between negative and positive quantities, with a slight inclination towards positive polarity. This is because the comments under the posts on these subreddits can be of both positive and negative emotion as the users are generally in a negative state of mind due to these mental health issues. However, the slight positive inclination shows that the users share positive comments more frequently in order to help and support each other. Figure 5a shows the combined results of polarity vs. number of sentences for all the subreddits. It can be seen that though there are significant number of sentences with negative polarity, the general inclination is towards positive interactions. Figure 5b shows the distribution of subjectivity and polarity for all the subreddits combined, and it can be inferred that for all subreddits, the user interactions are more subjective than objective in nature. Fig. 5a Polarity vs. no. of sentences in all subreddits combined b Distribution of Polarity and Subjectivity of all comments in all subreddits combinedFull size image For studying the sentiment of the author’s final comments, we analyze the polarity values obtained for the author’s last comment for every thread in each subreddit. Figure 6 shows the results on combining these values for each subreddit. We can see that the final comments are mostly of positive polarity, indicating that the user interactions positively affect the author and improve their state of mind, resulting in more optimistic comments from the author. Fig. 6Polarity vs. no. of sentences for author’s last comment in each subreddit a Anxiety b Bipolar c SuicideWatch and d DepressionFull size image Figure 7 shows the polarity vs. sentences for last comment on all the threads of all the subreddits combined. This also provides us the same inference that though there exist comments with negative polarity, maximum comments show a positive magnitude showing that the shift in emotional tone of the author is a positive one. Fig. 7Polarity vs. no. of sentences for author’s last comment all subreddits combinedFull size image The results in all the graphs above give us a qualitative overview of the effect of user interactions on the author’s emotional tone. [SEP] Justify:

Output: The text contrasts the claim by analyzing the emotional tone of comments in various subreddits. It indicates that while there are both negative and positive comments, the overall interaction shows a positive inclination. However, this analysis of sentiment suggests that understanding emotional tone is complex and indicates that AI tools may not be able to perfectly interpret this complexity given the mixed emotional states evident in the comments.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: Nearly all of the intact forest has been destroyed near the mines, the underground aquifers have been permanently damaged, rivers have been diverted away from communities, and there are dangerous levels of air and water pollution [41, 42]. As for the conflict, there were several violent actors in the department and, in contrast to Caquetá, paramilitary groups played a more significant role in Cesar. For example, between 1997 and 2006, the Drummond Company, a mining company, supported with money the leaders of the United Self-of Colombia (de Colombia, or AUC, in Spanish), who were located in the coal mining areas in the north of the department of Cesar. In addition, the of the AUC, under the leadership of Jorge 40, a member of the elite Cesar department, sought to capture elected offices in some coast departments, including Cesar [43]. Although land use changes in both departments have developed differently and differing land suitability, they have some similar characteristics that allow for the comparison of both departments. First, in both regions, resource depletion is associated with land accumulation and the expansion of the agricultural frontier. Second, both regions were highly affected by armed conflict and, for this reason, some territories within these two regions are included in the (PDETs, by Spanish acronym). These programs are an instrument that aims to stabilize and transform the territories most affected by violence, forced displacement, poverty, illicit economies, and institutional fragility in Colombia [44]. Thirdly, these departments present high rural land concentration. According to UPRA [45], Cesar and Caquetá are two of the five departments with the greatest rural properties and tend to have the highest variability and the largest median farm sizes. That is, properties in these departments are less similar in size. Fourth, most of Caquetá and Cesar have land tenure issues, with 58. 7% of rural land in Caquetá being technically and legally informal or imperfect; in Cesar it is 47. 43%; this makes it difficult to access institutional support [46]. Fifth, land use change in both cases resulted in the establishment of extensive pastures for cattle ranching. Sixth, in both regions there is a growing interest in developing other crops, including cocoa. Seventh, and finally, inequality in access to rural land is high for both departments. Thus, the Gini index for 2014 in Cesar was 0. 7 and for Caquetá it was 0. [SEP] Justify:

Output: The text does not relate to the claim about nature sounds enhancing peace and productivity. Instead, it discusses environmental degradation caused by mining activities, land use changes, and conflicts in specific Colombian regions, which is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: 042) used to quantify the motor recovery status. One year later, (Mekbib et al. 2021) conducted an RCT of the same designed system. Twenty-three participants were randomly assigned to a VR group (n = 23, IVR-group n = 12; control group n = 11). Both groups significantly improved the (BI) (p < 0. 05), reflecting the recovery of UL motor function. The IVR-group revealed more significant improvements in FMA-UE scores (p < 0. 05) than in the control group. Neural activity increased after the intervention, particularly in brain areas involved in the recovery of motor functioning, such as the primary motor cortex. The only study with children was carried out by Bortone et al. (2020) and aimed to determine the efficacy of immersive and weaRable hAptic devices (VERA) for rehabilitation of ULMI in children (n = 8) with CP and developmental dyspraxia (DD). A two-period cross-over design was adopted for determining the differences between the proposed therapy and CR. Eight children were randomised into two groups: one group received the VERA treatment in the first period and the manual therapy in the second period and vice-versa for the other group. Results show both groups significantly improved their performance. No statistically significant differences were found between the two groups. The study suggested that IVR and wearable haptic devices are a viable alternative to CR for improving upper limb function in children with neuromotor impairments. This review of related works has allowed us to conclude that VR can be used to improve ULMI rehabilitation, but that not much is known about the impact in the paediatric population, and that no studies have evaluated the feasibility, acceptability and perceived effectiveness of using an IVR system in particular for home rehabilitation and with children. 3 Methods3. 1 ParticipantsEthical approvals were obtained from (London—(IRAS Ref. 274,257)) and (Ref. ER19710920). Permissions were also gained from local and Development (R&D) (Ref. SCH-2540). We recruited participants aged 7–16 from Sheffield Children’s NHS (FT), who had sustained ULMI requiring rehabilitative care. [SEP] Justify:

Output: The text corroborates the claim by discussing a study that investigated the use of virtual reality (VR) in rehabilitation for patients with upper limb motor impairments. It mentions that both an immersive VR group made significant improvements in motor function compared to a control group, confirming the effectiveness of VR in physical therapy for regaining mobility. Additionally, it highlights that VR is suggested as a viable alternative for improving rehabilitation outcomes, which aligns with the claim.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: The overall positive inclination of the comments indicates that user interactions on these subreddits are helpful in positively influencing the user’s state of mind. The subjectivity analysis of the comments also gives us an idea about the nature of the comments on these platforms and shows that most of the comments are subjective, coming from user’s own opinions and emotions, rather than factual information. Next, we analyze the predictive modeling of this emotional shift. We plot the joint distribution for the values of true and predicted magnitudes of the MODEL against two other baselines as shown in the heat map in Fig. 8. 100 random threads from the test set as well as a Density estimator which has been color-coded, represented by circles. The sizes of the circles are proportional to the number of comments, which lie in the range of 2 to 64. The MEAN baseline outputs the average emotional tone in sequence S, and MEANS predictions are highly concentrated around [-0. 3, 0. 8]. The LAST baseline outputs the emotional tone of the last comment in S which contains a large range of prediction, but it is observed that it is concentrated along the diagonal in the Depression subreddit. The larger the vertical difference to the diagonal, more errors is produced, because of extremely negative responses within the subreddit. We see here in Fig. 8 that the extreme values are best predicted by MODEL. Fig. 8of joint distribution of true and predicted valuesFull size image We also use XGBoost, which is a gradient boosting bundle of decision trees, which perform with high performance and deliver accurate results in prediction tasks. XGB is used on Train, Test and Validation datasets, to see if the desired results are being achieved on the Test dataset after working on the Validation dataset. We observe that the TEST dataset outperforms the Validation dataset, which ensures that the proposed model is trained well, as shown in Fig. 9. Fig. 9Comparison of performance between train, test and validation dataset using XGBoost. Full size image 6. 2 Quantitative resultsWe abbreviate each subreddit as follows: Anxiety as ANX, Depression as DEP, SuicideWatch as SUI and Bipolar as BIP for simplicity. Comparing various baselines in order to produce more accuracy and efficiency, we obtain results in terms of the Weighted L1 Loss that deals with extreme responses, as shown in Table 2. performs better than all the other baselines by at least 12. [SEP] Justify:

Output: The text contrasts the claim by highlighting that the subjectivity analysis shows that comments stem from personal opinions and emotions rather than factual information. It indicates that there are limitations in predicting emotional tone accurately, as it discusses various baselines and errors that arise in models, particularly in context with negative responses. Specifically, it points out that larger vertical differences from the diagonal lead to more errors, suggesting that AI tools may struggle to interpret emotional tone perfectly.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: 6 [45]. This index is one of the most widely used indicators reflecting the level of inequality in land distribution. The indicator shows how the land area is distributed among its owners. Values close to one indicate high inequality in property distribution. Egalitarian distributions would show a Gini index close to zero, where, for example, 10% of the owners have 10% of the area. The estimation for Colombia as a whole is even more drastic than in the two case studies, at 0. 8789, which represents very high inequality in the property land distribution [45]. Materials and methods System dynamics and Diagrams (CLDs) System dynamics, widely believed to be critical for handling the complexity facing the world, comprises a set of conceptual tools that enable understanding the structure and dynamics of complex systems [47]. In other words, system dynamics allows for taking a problem apart and reassembling it to understand its components and causal relationships [48, 49]. CLDs are a useful tool within this approach, helping to provide a broad range of insights and implications [50] that can be used as the basis for developing actions and implementing policy [51]. CLDs link key elements, highlighting the causal relationships between them through loops. By stringing together several loops in these diagrams, it is possible to visualize and explain a logical interconnected chain of facts that creates a story about a complex situation and that even shows systemic failures. In this context, a systemic failure refers to a failure in one part of the system or parts of the system that propagates through the whole system and impacts the entire interconnected chain of social, economic, and environmental events [52]. Methodological approach Here, we describe the four steps taken to build and validate the regional CLDs using primary and secondary sources in order to understand their land-use dynamics (Fig 2). All participants involved in the study were informed of its objectives and they gave their verbal informed consent to participate in the interviews or workshops. The study was approved by the Board (IRB) of the Alliance Bioversity-CIAT, which complies with international ethical standards. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 2. Methodology. research was principally conducted by a group of Colombian experts on sustainable land uses. As a first step, to advance the existing knowledge within the group, we collected other experts’ knowledge insights on several issues related to land use dynamics of the study regions. [SEP] Justify:

Output: The text discusses land distribution inequality and a methodological approach for studying land-use dynamics in Colombia. It does not address or provide any information related to nature sounds, their effects, or how they influence environments, thus making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: 1 Goniometer: range of motion resultsThe OT measured the ROM of the affected upper limb joint before and after exposure to IVR (5–10 min) and the unaffected upper limb to have a comparative value of the usual movement without an injury. As shown in Table 2, most, though not all, of the affected area ROM readings showed improvements in movement post-VR therapy. The remaining readings indicated unchanged movement (Pt 5 wrist pronation, radial and ulna deviation, patient 6 wrist radial and ulna deviation and Pt 8 shoulder external and internal rotation). Table 2 Descriptive pre-VR, post-VR and unaffected ROM dataFull size tableCompared to healthy limb ROM measured at the same joint area, five of the eight patients achieved post-VR measures equal to the usual degrees of motion at some joint assessed (Table 2). 4. 2 Paediatric quality of life inventory resultsPedsQL results are shown in Tables 3 and 4. On each dimension and as an overall measure, post-VR scores showed statistically significant improvements (p ≤ 0. 05). Table 3 PedsQL pre-post: SummaryFull size tableTable 4 PedsQL pre-post: SummaryFull size table4. 3 System usability scale resultsThe direct item scores were transformed, summed and converted to 0–100. The mean obtained by the patients was 99. 64 (n = 7), demonstrating high usability above the standard mean score of 68. In addition, patients strongly agreed with items such as "I think I would like to use the VR system frequently", "I found the VR system easy to use" and "I felt very confident using the VR system". Items 4 and 10, referred to as the learnability dimension, received a direct score (0–4) of 4 and 3. 43, respectively, showing that the VR system was easy to learn. In addition, patients reported not needing technical assistance before using the system. 4. 4 Interview resultsQuantitative data from the Likert questions showed that, in general, patients reported no difficulties in setting up and using the game, nor did they perceive pain when using it, with high levels of enjoyment as shown in Table 5 (M = 9. 29, ST = 0. 951; M = 3. 17, ST = 1. 60; M = 1. 33, ST = 1. 75: M = 9. 00, ST = 1. 29). [SEP] Justify:

Output: The text corroborates the claim by providing evidence of patients showing improvements in range of motion (ROM) after exposure to virtual reality (VR) therapy. It details how the OT measured the ROM before and after VR exposure and notes that most affected areas showed improvements in movement post-VR therapy. Additionally, the text mentions that five of the eight patients achieved post-VR measures equal to the usual degrees of motion at some joint assessed, indicating that VR is utilized in therapy to help patients regain mobility through guided exercises.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: 1%. Table 2 Result with respect to weighted L1 lossFull size table Prediction examples We take an example thread from the subreddit Depression, where the model has accurately predicted the final emotional tone 0. 43 for the thread author’s final emotional tone 0. 33. This also shows how the emotional tone has improved from − 0. 11 to 0. 42 on receiving positive feedback and support from their peers. We can clearly observe the same from the Table 3 below. Table 3 Example of user interaction and subsequent emotional tone progressionFull size table 7 ConclusionsWe address the topic of predicting progression in users’ emotional tone (a substitute for emotional state) following conversations in mental disease online forums in this work. Sentiment analysis using TextBlob and VADER shows that the final emotional status of the authors is rendered positive after being subjected to interactions on the subreddits. The results of our prediction model showed that, despite the task’s inherent difficulty, a possibility exists, to predict how users will react to interactions on these mediums. The qualitative result analysis shows that the TEST dataset outperforms the validation dataset and hence it indicates that the model is well-trained. The quantitative analysis shows that the MODEL transcends the Mean and Last baselines by at least 12. 1%. The models we’re considering don’t need any personally identifiable information specific to a user, so we can deploy these models while avoiding any privacy concerns. They are also advantageous and relevant for newcomers to a community. New systems can be employed which can make correct predictions to help users in writing comments, increasing their chances of having a good impact on their readership. Furthermore, the prediction model can be improved by integrating attention-based models, RNNs, Transformers and Network models. Data availability The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. 1605. 04462(2016) Large-scale analysis of counseling conversations: an application of natural language processing to mental health. (2020). In: (eds), Networking and Applications - Proceedings of the 33rd on Networking and Applications AINA-2019. Springer Verlag. Bárbara da Silva APC (2021) Predicting user emotional tone in mental disorder online communities. [SEP] Justify:

Output: The text contrasts the claim by discussing the challenges and limitations faced when predicting emotional tone in users' interactions on online forums. While it mentions some successes, such as improvements in emotional tone from interactions, it emphasizes the task's 'inherent difficulty' and acknowledges that predictions are not perfect, indicating that AI tools do not achieve a perfect interpretation of emotional tone and intention.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: For this, we conducted four initial qualitative in-depth semi-structured interviews in December 2019. To consider diversity of knowledge and experience in the research topics, the criteria to select the experts were: (1) experience on activities related to land use dynamics in the areas analyzed; and (2) knowledge about land tenure systems. Therefore, we selected experienced experts on development cooperation projects, representatives of NGO’s and community-based organizations. The first interviewee was a practitioner with experience in implementing land formalization and restitution projects around Colombia. The second interviewee was a representative of a local NGO in Caquetá with knowledge and experience on the patterns of land-use change and deforestation in the Amazon region. The third interviewee was a farmer and social leader, who has been involved in sustainable rural development and social movements against land grabbing in Cesar. The semi-structured interviews included three guiding questions: (1) what is your perception about land informality and land restitution processes in each department? ; (2) what are the current land use conflicts that are affecting each department? ; and (3) do you know formal institutions or mechanisms to solve land use conflicts in each department? Each interview lasted between 60 and 90 minutes. All interviews were transcribed and data analyzed using qualitative content analysis, a method to identify manifest and latent structures in texts and other qualitative material [53, 54]. Secondly, based on the expert insights we conducted a literature review to identify key elements and causal relationships on the main land-use dynamics issues in each department. and Ison [52], we retrieved information from two sources: peer-reviewed 1. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageTable 1. Key entry points on land use dynamics in Caquetá and Cesar. overview shows land use conflicts in Caquetá are heterogeneous and depend on if they are in the foothills or not. There are different factors that influence these conflicts, among them: armed conflict, unsuitable land uses, competition between land uses or an overlap between these different factors. On the other hand, land grabbing is one of the ways to launder money and therefore the issue of illicit crops is related to deforestation, conflict, cattle ranching and unsustainable land uses. Thus, the promotion of sustainable land uses in the department is related to the legality of land tenure. [SEP] Justify:

Output: The text provides detailed information about qualitative interviews conducted concerning land use dynamics, expert knowledge, and land tenure systems, but it does not address or relate to the claim that nature sounds can enhance the peace and productivity of an environment. As such, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: Table 5 Descriptive results interview quantitative questions to the patientsFull size tableQualitative comments from all 15 participants (7 patients, 7 parents and 1 OT) demonstrated positive impressions of and positive attitudes towards IVR during ULMI rehabilitation (Table 6). Parents (6/7) found the IVR game an excellent idea that keeps them doing the necessary physio exercises. They also thought it would have a good place in the clinic in the future, not just for ULMI rehabilitation but also for other pathologies. The OT also considered that the IVR system could be helpful in different areas. She thought that it would be asked to be used again by patients and parents, those who already tried it, and others new ones that could come to the service. Table 6 Data extracts: General impressionsFull size tableThe content analysis generated two main themes. One theme related to “System Playability” was characterised by a process of “Learning and Mastery”. The second theme focussed on “Comparison of IVR with CR” and included sub-themes of: “Natural movements” and “Motivation to engage” (Fig. 5). Data extracts can be found in Tables 7, 8 and 9. Fig. 5Content analysis themes from the patients, parents and OT interviews: “System Playability” and “Comparison of IVR with CR”Full size imageTable 7 Data extracts: System Playability: Learning and MasteryFull size tableTable 8 Data Extracts: Comparison of IVR with CR: Natural movementsFull size tableTable 9 Data extracts: Comparison of IVR with CR: MotivationFull size table4. 4. 1 Natural movementsIVR rehabilitation aims to facilitate the specific movements recommended by OTs in CR. In this study, the OT stated that this IVR intervention successfully reproduced the required exercises and combined all the movements she was looking for. Parents (5/7) observed that when their child was immersed in the game, he performed movements more fluently and naturally, without realising it. Similarly, most patients (4/7) and parents (6/7) indicated that the game made rehabilitation exercises easier to complete. This ease seemed to reflect both fluency of movement and lack of pain and fear. Reported pain levels were low (M = 1. 33, ST = 1. 75). [SEP] Justify:

Output: The text corroborates the claim by discussing how interactive virtual reality (IVR) is employed in rehabilitation, specifically mentioning that it facilitates the specific movements recommended by occupational therapists (OTs) during conventional rehabilitation (CR). It highlights positive attitudes towards IVR for enhancing patient engagement and making exercises easier and more fluently executed, thus supporting the claim that VR aids in regaining mobility through guided exercises.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: 125:641–651(2010) Subjective versus objective: an exploratory analysis of Latino primary care patients with self-perceived depression who do not fulfill primary care evaluation of mental disorders patient health questionnaire criteria for depression. 12(5):PCC. 09m00899(2018) Norms matter: Contrasting social support around behavior change in online weight loss communities. In: on in Computing Systems, Association for Computing Machinery, pp 1–14(2016) Discovering shifts to suicidal ideation from Content in Social Media. (2016) Discovering shifts to suicidal ideation from mental health content in social media. In: on in Computing Systems, ACM, pp 2098–2110Devlin J, Chang M-W, Lee K, (2019) BERT: Pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the 4186. Accessed 15 Apr 2022 (2017) Characterisation of mental health conditions in social media using informed deep learning. 7:45141225. Retrieved from Accessed 3 Apr 2022(2018) Hierarchical neural model with attention mechanisms for the classification of social media text related to mental health. of the on : to Clinic. LA. Association for Computational Linguistics, New Orleans, pp 69–77. Accessed 23 Mar 2022(2019) Evaluating the predictability of medical conditions from social media posts. PLoS One 14(6):e0215476Park A, (2018) Harnessing reddit to understand the written communication challenges experienced by individuals with mental health disorders: analysis of texts from mental health communities. J Res 20(4):e8219(2020) Social media reveals psychosocial effects of the covid-19 pandemic, (2019) DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. H-é (2018) Expert, crowdsourced, and machine assessment of suicide risk via online postings. In: Proceedings of the on : to Clinic. Association for Computational Linguistics, New Orleans, pp 25–36. Accessed 16 Mar 2022B, Couto da Silva AP, (2018) Online social networks in health care: a study of mental disorders on reddit. IEEE/WIC/ACM on (WI)TextText Processing-. [SEP] Justify:

Output: The text contrasts the claim as it discusses various studies related to analyzing mental health content in social media and does not provide evidence indicating that language translation AI tools can perfectly interpret emotional tone and intention. In fact, the focus on mental health content signals the complexity of understanding emotional states, which suggests that accurate interpretation by AI tools may be limited.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: In the case of Cesar, poor land use planning and public policy promoted crops such as cotton and oil palm in the department. These types of unsustainable uses degraded the land and resulting in an excess of depleted land dedicated to extractive and extensive cattle ranching. On the other hand, equity in access to water is a fundamental issue in this department. It is notable that the conflict in Cesar is closely related to the issue of land accumulation and concentration. Systemic implications of land use conflicts in Caquetá Fig 3 depicts land use conflicts in Caquetá through four reinforcing loops related to (R1) agricultural land-use conflicts and deforestation, (R2-R3) their implications on the land tenure system; and (R4) climate change. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 3. Causal loop diagram of land use conflicts in Caquetá, Colombia. Key elements are joined by arrows indicating where there is a causal relationship between them. A (-) sign adjacent to an arrow indicates that the cause has a negative effect; if the cause has a positive effect there is no sign. The encircled R in each loop center means that the loop is a reinforcing loop (positive feedback). The equal sign located on the arrows symbolizes a delay in the system. has historically generated conditions fostering legal and illegal land colonization. This process, which has been poorly planned and uncontrolled, led to the deforestation of the Amazon rainforest [57, 58]. Nowadays, Caquetá is one of the most deforested departments in Colombia. Overall, Colombia lost 197. 159 ha of forest in 2018, and for Caquetá alone that value was 46,000 ha. This department ranked first in deforestation, followed by Meta (44,712 ha), Guaviare (34,527 ha) and Putumayo (13,903 ha), all of them are located in the same geographical region [59], among other examples. In most cases, this deforestation is caused by external settlers who expand the agricultural frontier by clearing the tropical forest, which in turn triggers the establishment of unsustainable land uses, such as illicit crops, mining, and extensive cattle ranching [23, 60–62]. As the land is not suitable for these uses, its poor productive capacity is depleted and deforestation continues [63], as depicted in the reinforcing loop R1. [SEP] Justify:

Output: The text is irrelevant to the claim since it discusses issues related to land use, deforestation, and agricultural practices in Colombia. None of the information pertains to the effects of nature sounds on environments or productivity.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: Qualitative data from parents suggested that they (6/7) did not witness pain in their children and perceived that children were not conscious of doing the rehabilitation exercises. Parent 8 reported that IVR reduced the fear and limitation of movement in her child with an external fixator, thereby helping her move naturally and unconsciously. As a result, she realised that she could do more than she had previously thought and achieved a better range of motion. 4. 4. 2 Motivation to engagePatients (5/7) believed they would be more likely to complete their rehabilitation exercises with the IVR game at home. The IVR positively influenced their motivation and intention to carry on with the rehabilitation (6/7). Four noted that IVR rehabilitation was more fun and less boring, and quantitative data demonstrated high levels of enjoyment amongst participants (M = 9, ST = 1. 30). Linked to motivation, the frequency of use was high. Three out of seven patients used it every day for between 10 and 20 min. One patient stated that they used it at least twice a day. In only one case, a participant (Pt 4) reported reducing the frequency of use after the first week due to repeatedly playing the same games. The greater motivational effects of IVR resulted in some parents (3/7) feeling less that they needed to remind and motivate their child with exercises. OT perceptions supported these findings that patients found the IVR game more interesting, engaging and motivating than usual exercises and that movement had improved. The best bits of the game reported by the patients were: shooting the arrows at the gnomes; seeing the score improve; rock climbing and falling; feeling challenged; being able to do different activities; graphics and animation. They also enjoyed being present in a virtual environment that they had never experienced previously. There were no worst bits reported from most patients (5/7). However, one patient (1/7) expressed that the worst was to have to do the levels before you can get onto the climbing one (Pt 2), and another (1/7) said that there are not that many games on it (Pt 4). Data extracts are found in Table 9. 5 Discussion, limitations and future line of studyChildren and adolescents with ULMI often undergo a long-term, demanding and challenging rehabilitation process to recover motor functionality (Liebs et al. 2020). [SEP] Justify:

Output: The text corroborates the claim by providing evidence that immersive virtual reality (IVR) positively influenced patients' motivation to engage in rehabilitation exercises. It mentions that IVR helped reduce fear and limitations of movement, thus aiding patients in moving naturally and unconsciously. Parents noted that their children experienced a better range of motion and found the IVR games more interesting, engaging, and motivating compared to usual exercises. The findings suggest that IVR is an effective tool in physical therapy, supporting the use of virtual reality to assist patients in regaining mobility.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: -19 PreprintsProtocolsVideosJournalsTools & a 10. 21203/rs. 3. rs-2576109/v1This work is licensed under a CC BY 4. 0 LicenseStatus:Published18 Apr, 2023Read the published version in →Version 1posted 3You are reading this latest preprint versionAbstractIn order to enable students to directly face empirical data, summarize translation rules and learn translation skills, this paper studies the basis, motivation and methods of applying research dynamics in translation and teaching. Presenting data in class is the main method of dynamically searching corpora, which enables learners to face enough bilingual data that are easy to choose, and makes translation skills and teaching of translation of selected language items relatively focused. In recent years, the emotional analysis text has attracted academic scientists, and the professionals involved in the research, the use of research methods, and the cultural background related to language have become more and more extensive. In this paper, natural language processing is used to analyze emotions contained in translated texts. Natural language processing not only helps to manage the huge ability of data to efficiently translate text, but also helps to extract the hidden emotions in text translation. It only takes half the effort to achieve the multiplier effect. The multi label classification in natural language processing can reflect the information contained in emotion. The translated text is more detailed, which is helpful for further research. corpusNatural language processingCultural translationEmotional analysisFiguresFigure 1Figure 2Figure 3Figure 41. IntroductionAlthough the research on corpus based translation teaching has achieved preliminary results, there are still many problems about its value in translation teaching and possible resources and means [1]. Corpus based translation research has not solved the problem. From the macro and micro perspectives, translation teaching research is an unsolved translation teaching model; From a micro perspective, "the consistency between parallel corpora, translation and teaching has not been solved", and the establishment of a parallel corpus directly serving English and Chinese translation and teaching has not been effectively carried out [2]. In this paper, a learner centered cultural translation model based on dynamic search corpus is established. In addition, by guiding students to use programs to research and retrieve practical data, we can build a modern learning environment and cultivate students' self-learning ability, so as to improve their ability to practice translation in real situations [3–4]. Emotional analysis in text translation has become a hot research direction in the research [5–6]. [SEP] Justify:

Output: The text contrasts the claim by highlighting the challenges faced in translation teaching and indicating that emotional analysis in text translation is still an area of active research, suggesting that current tools may not perfectly interpret emotional tone or intention. Specifically, it notes that while natural language processing assists in managing data and extracting emotions from translations, there are still many problems related to translation teaching models and the establishment of parallel corpora for effective translation practice.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: The process of agricultural frontier expansion is an essential element stimulating the land grabbing schemes in the department where settlers invade the land, mainly for converting forest to pastures for cattle raising to get a formal title, and which is subsequently exploited by large landowners who buy the titles [20]. This process exacerbates the well-known problem of land tenure insecurity and concentration that, in turn, increases inequality and poverty since smallholders lack capital and credit to buy already cleared lands. These land-related problems create a perverse incentive for expanding the agricultural frontier by clearing more forests [26], as reinforcing loop R2 shows. Reinforcing loop R3 illustrates the implications of land grabbing, which in Colombia is considered to be a way for large investors and armed actors to transform illegal assets into legitimate capital [64]. This process generates land speculation that diminishes land governance due to power asymmetries and land inequality, thus the lack of governance over natural resources in the region facilitates increasing deforestation. The reinforcing loop R4 reveals how the ongoing Amazon deforestation creates a set of negative environmental effects, including the increase of greenhouse emissions [65], biodiversity losses, and water cycle changes, that subsequently exacerbates climate change. These changes could intensify the deforestation in the long term, since climate change, droughts and rising temperatures may contribute to the death of vulnerable trees in the forest, thus creating a new cycle causing further deforestation [66]. Systemic implications of land use conflicts in 4 shows the systemic structure of land use conflicts by means of different reinforcing loops regarding unsustainable land uses and land degradation (R1), climate risk in agriculture (R2), land productivity and water management (R3), forest conservation, agricultural frontier and resource depletion (R4) and land tenure system (R5). Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 4. Causal loop diagram of land use conflicts in Cesar, Colombia. Key elements are joined by arrows indicating where there is a causal relationship between them. A (-) sign adjacent to an arrow indicates that the cause has a negative effect; if the cause has a positive effect there is no sign. The encircled R in each loop center means that the loop is a reinforcing loop (positive feedback). The equal sign located on the arrows symbolizes a delay in the system. reinforcing loop R1 exhibits how land productivity is directly affected by land degradation, which is evidenced by the increasing soil erosion in the region. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses issues related to agricultural frontier expansion, land grabbing, deforestation, and their implications on land tenure and environmental factors. It does not mention nature sounds or their potential effects on creating peaceful or productive environments.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: Home-based therapy with VR has been shown to offer greater accessibility, delivery and early rehabilitation to improve functional outcomes and quality of life (Su et al. 2021; Thielbar et al. 2020). This study aimed to explore whether IVR could offer a feasible solution for the rehabilitation of children with ULMI at home. Using quantitative and qualitative approaches, we found that IVR has clear potential to be a successful solution for physical rehabilitation for children with ULMI. More importantly, our findings suggested that IVR appeared to be very effective as a self-directed home therapy for this clinical population. In summary, our results indicated that IVR for ULMI home rehabilitation could: (1) be easy to learn and acceptable, (2) improve motor function, (3) reduce the difficulty in the reproduction of therapeutic movements, (4) be motivating and enjoyable and (5) improve quality of life. The ROM (Goniometer) data suggested that IVR rehabilitation could improve shoulder, wrist and elbow motor functionality, enhancing flexion, extension and abduction movements. The patients demonstrated ROM gains, in some cases even recovering the same degree of movement in the injured limb as the unaffected limb. These data are promising, indicating that all paediatric patients who have used our IVR game have improved their affected limb’s range of motion. Quality of life (PedsQL) scores also indicated a significant improvement after the IVR home trial compared to baseline scores. Physical and psychosocial health scores improved after the study, which may reduce the risk of long-term diseases such as chronic pain and disability (Cambiaso-Daniel et al. 2017; Liebs et al. 2020). The usability test (SUS) scores showed that patients generally understood the game mechanics well, and there were no critical errors that would have impeded the gameplay. For example, based on the patient's subjective report, no difficulty was found in setting up and getting used to the game. In this sense, we must point out the relevance of having the OT at the initial session, where they were shown how to use the game. Therefore, we encourage researchers and clinicians when proposing a self-directed session for children at home to include a first contact with the game accompanied by the OT or other healthcare professionals delivering the therapy. In addition, we recommend offering follow-up or support via telephone or email to solve potential problems during home ULMI rehabilitation. [SEP] Justify:

Output: The text corroborates the claim by detailing how immersive virtual reality (IVR) is utilized in home rehabilitation, specifically for improving functional outcomes and quality of life for children with upper limb motor impairments (ULMI). It highlights that IVR can improve motor function, enhance range of motion (ROM), and make therapy motivating and enjoyable. The study results indicated that patients experienced significant improvements in arm functionality and quality of life after engaging in IVR therapy, thereby supporting the efficacy of virtual reality in physical therapy for regaining mobility.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: This research focuses on the translated text, including the analysis of text features and the relationship between content and emotional information. The purpose of this study is to explore the emotional expression in the translated text, understand and recognize the emotional information in the translated text [7]. The main direction of this research is to understand and analyze the emotional information contained in the translated text. The emotion analysis of translated text can help devices understand human emotions more accurately and intelligently through natural language, and provide technical support for the future development of human-computer interaction [8]. 2. Related WorkThe literature studies the construction and application of learner translation, and attempts to build a method based on translation teaching and translation model evaluation [9]. The literature points out that with the progress of deep learning technology and the continuous improvement of various aspects of graphic computing, especially the storage and computing capabilities, people began to use computers to simulate artificial neural networks on a large scale [10]. At the same time, with more research, natural language processing has made more outstanding achievements in important fields. The literature proposed that text emotion analysis is a special classification of problem text [11]. The purpose of text analysis is to extract a summary of emotional information from the text, which is usually difficult to obtain and process from the information. More emotion analysis tasks are divided into three parts: emotional information extraction, classification, retrieval and inference. The literature focuses on corpus tagging to broaden the application of corpus in translation teaching, and discusses how to build a corpus, as well as a self created corpus dual mode tagging system and tagging extraction tools [12]. By comparing the translation quality between the two teams, the literature finds that a group of students who use the research dynamic group to teach translation are better than those who use traditional teaching methods in terms of terms and expressions in understanding topics and choosing translation. Since the middle of 1990, great progress has been made in natural language processing [13]. With the development of Internet technology, the significant increase of computing power and hard disk storage space provides basic equipment for natural language processing research. Information extraction and retrieval based on natural language processing become more and more important [14]. During this period, natural language processing entered a relatively mature stage, and a set of methods based on technical rules began to be applied to machine translation in this field. A neural network algorithm for web page classification is proposed in the literature [15]. The experimental results show that the neural network is more accurate than the traditional learning machine based on the classification algorithm. [SEP] Justify:

Output: The text contrasts the claim by highlighting the complexity involved in interpreting emotional tone and intention in translated text. It discusses how 'emotion analysis of translated text can help devices understand human emotions more accurately,' suggesting that current tools may not perfectly understand emotional nuance but are progressing toward that goal. Thus, it implies limitations in the capabilities of AI in interpreting emotional content fully rather than affirming the claim.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: The probability of keeping productive systems in areas with desertification and overexploitation processes is very low [67]. In 2021, Cesar has some of the most degraded soils in Colombia, with 81. 9% of erosion. This degradation by erosion specifically affects agricultural yields, with 60. 4% of all agricultural sites eroded to some extent [68]. Due to the non-vocational use of land, productivity constraints are increasingly evident because people incorrectly believe they can adapt soils to agricultural uses instead of the other way around [68]. With regard to the effects of erosion on climate change, as illustrated in the reinforcing loop R2, FAO [69] points out that the loss of soil organic carbon not only negatively affects soil health and food production, but also exacerbates climate change and the risk of damage in the agricultural sector. [70] remarks, agriculture is deeply interconnected with weather and climate, making this factor dominate in the overall variability of food production and a continuing source of disruption to ecosystem services and facilitator of land use conflicts. Concerning the reinforcing loop R3, unsustainable land uses in the region has also affected water availability. Inadequate patterns for access, occupation, and use of natural resources, as well as poor technological practices, are threatening their valuable natural endowments [42]. Currently, the water deficit and the low water quality in mining zones represent a critical future scenario for the preservation of fauna and flora, for food security and for the development of agricultural value chains, such as palm oil, coffee, livestock, and cocoa, among others [42, 71]. Under climate change scenarios, with more severe droughts, water accessibility problems increase risk in the agricultural sector. Another cascade of impacts are found when looking at the effects of decreasing agricultural productivity on the conservation of tropical dry forest remnants, as depicted in the reinforcing loop R4. In Cesar, strategic ecosystems, such as tropical dry forest and swamplands, lack a management strategy that takes into account their conservation, ecologic dynamics and ecosystem services [67]. Therefore, they are heavily degraded, as a result of the diverse pressures that human beings have exerted on it, including deforestation with the purpose of economic exploitation, coal mining, agricultural expansion, and cattle ranching [39, 41, 42, 72, 73]. Finally, the cascade of failures in the reinforcing loop R5 highlights the lack of appropriate land use planning that takes into account the land suitability. [SEP] Justify:

Output: The text discusses various factors affecting agricultural productivity and land degradation in a specific region of Colombia but does not mention nature sounds or their impact on peace and productivity. Therefore, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: Furthermore, the positive results in learning and mastering the game may be explained by the inclusion of a tutorial at the beginning of the game, based on the findings of our previous study (Phelan et al. 2021a, b). As a result, children learned to reproduce the basic movements, and interaction mechanics were adapted to their capabilities, such as achievable range of movement. This is in line with current research, which demands games that allow the customisation of game variables to the individual’s difficulties (Brusque et al. 2018; Zahabi, Mohammed, and Razak 2020). Another key element that helped avoid patient confusion was the inclusion of a companion that guides the player and acts as a narrator of the story. The companion was effective in the delivery of the narrative to create a more believable and engaging world. Also, consistent visual cues were added to interactable objects, and audio cues were incorporated to direct the player's attention. On the other hand, the qualitative results have contributed to detecting some IVR system usability improvement opportunities. Younger children (7–12 years old) reported they found it harder to get used to the game, whilst adolescents (aged 15–16) would like additional levels. This underpins future challenges in the development of IVR systems to support therapy across a broad age range of children. We recognise the need to maintain a certain difficulty level whilst being stimulating and providing meaningful activities during physical rehabilitation to ensure compliance, especially for children. There is scope for further development to ensure the right level of challenge and mastery for children of all ages. We plan to offer a broader range of difficulties in future iterations to ensure the enjoyment of those children who find it more difficult (e. g. younger patients in the early recovery phase or with complicated clinical conditions). In addition, this could positively affect self-confidence, self-esteem, attention span, concentration and interest in learning and, thereby, help to maintain motivation and compliance, as noted by previous researchers (Meyns et al. 2018; Wenk et al. 2021). The OT reported that getting used to the game with the younger patients was challenging. As a result, the OT requested a way for the professional to monitor the system in real-time, observing what patients are seeing to better help and guide them in cases where they are younger or if they cannot make progress. Future development will consider this aspect. [SEP] Justify:

Output: The text corroborates the claim by discussing the use of an interactive virtual reality (IVR) system in a therapeutic context. It mentions how younger patients faced challenges learning to use the game, which aligns with the idea of guided exercises in therapy that need to be tailored to individual capabilities. It highlights the role of a companion in guiding the player, which parallels the guidance necessary in physical therapy. Furthermore, it emphasizes the importance of maintaining an appropriate difficulty level to ensure compliance during rehabilitation, thus supporting the utility of virtual reality in helping patients regain mobility.


Input: Task: contrast the claim using the given text. Claim: Most language translation AI tools can perfectly interpret emotional tone and intention. [SEP] Text: They create a discovery based learning environment for students, so that students can make full use of their initiative and self-learning ability, use dynamic research and software retrieval to translate typical, real, rich observation, analysis and thinking examples, and then the interaction between teachers and students to discuss language features, Translate translation methods and techniques into two ways. In order to evaluate translation quality, teachers can guide students to use relevant statistical data retrieval procedures to judge translation quality and style more comprehensively and objectively. According to the latest catalog issued by CSSCI in January 2022, 378 translation research papers were obtained from 15 foreign journals (including the expanded version), which were selected as the source of CSSCI database. The topics are "Corpus" and "Corpus Translation". The two topics were searched in the journal. After manual differentiation, the meeting notice and the documents not related to corpus translation research were deleted, and 378 papers related to corpus translation research were obtained. Taking time as the horizontal axis, the research trend of corpus translatology is shown in Fig. 1, based on the name and real nature of all documents. textbooks are taken as the main collection objects of dynamic corpora, including the new HSK test text corpus released by the National Hanban, as well as ordinary natural corpora and classic Chinese textbooks for primary and secondary schools. The current scale is close to 200000 sentences. 1 for composition ratio. Chinese textbook corpus is an important part of dynamic corpus. This set takes into account such attribute characteristics as textbook type, application level, publishing age and influencing factors. Table 1 Composition of content Number of statements Proportion 1 of 140000 sentences 65. 7% 2 of HSK 21000 sentences 9. 9% 3 Language materials of natural literature 40000 sentences 18. 8% 4 Corpus of Textbooks 12000 sentences 5. 6% The two translations of the same 2. Table 2 Comparison of of Translation 1 and Translation 2 function word Translation 1 Translation 2 Key value Significance 1 however 79 15 47. 10 0. 000 2 but 7 58 -46. 37 0. 000 3 from then on 63 16 29. 38 0. 000 4 from 19 57 -20. 38 0. 000 5 I 140 34 68. 27 0. 000 6 We 67 26 18. 25 0. 000 7 this 60 107 -14. 03 0. 000 8 of 1345 1112 20. 45 0. [SEP] Justify:

Output: The text contrasts the claim by discussing the methods and challenges involved in evaluating translation quality and style, indicating that such a precise understanding of emotional tone and intention is not inherently guaranteed. It outlines a complex research environment for translation that doesn't suggest that AI tools can flawlessly interpret nuances, as it focuses more on the statistical and procedural aspects of language translation rather than on emotional nuances.


Input: Task: pass the claim using the given text. Claim: Nature sounds can make any environment more peaceful and productive. [SEP] Text: This precarious land use planning, including land tenure, land access, and land distribution, alongside the current land restitution programs, has also led to land accumulation with unsustainable uses and, consequently, with more soil degradation by erosion [68]. This last social reinforcing loop related to the land tenure systems is particularly important in Cesar since the inequality in land access helped to consolidate extractive activities and palm oil monocultures, which in turn represented a driver for disputes between armed actors for territorial control and resource extraction [74–76]. Currently, the land tenure issues as land restitution process to displaced victims of the conflict show a slow progress in Cesar. For example, the department has the highest level of land dispossession and has the fifth largest number of requests for land restitution outstanding at the national level, thus perpetuating the insecure property rights situation [76–78]. DiscussionWe map and compare the complexity of the problems related to land-use dynamics in two conflict-affected territories using CLDs. Neither diagram represents a screenshot of a current situation, rather they show how a series of factors that are separated by location and/or time might interact to create systemic failures. By using this tool, we are able to compare the two regions, identifying not just context-dependent characteristics but also systemic common drivers and trends of land-use changes. Land use changes in conflict-affected territories in Colombia involve complex system where everything is connected to everything else. Causal loops diagrams allowed us to conceptualize and construct our circular connections, mutual causality and the feedbacks in our problem. They are grounded in the theory of nonlinear dynamics and their feedbacks suggest that everyone shares responsibility for problems generated by a system. Thus no “one” factor is solely responsible for changes in the land use system [79–82]. A common driver of land-use change has to do with land access and distribution problems, which translate into a high land concentration in both regions. However, it is the result of dissimilar pathways that have been followed in each region. Land grabbing by clearing forests is how land is accumulated in Caquetá for speculative purposes. Unfortunately, this process was exacerbated following implementation of the peace agreement due to the power vacuum resulting from the demobilization of the guerrillas [23, 57, 83, 84]. Land dispossession caused by forced displacement is the way to accumulate lands in Cesar, which are then converted into economic exploitation areas. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses complex issues related to land use planning, land tenure, and land distribution in conflict-affected territories, without any reference to nature sounds or their impact on environments.


Input: Task: corroborate the claim using the given text. Claim: Virtual reality is used in physical therapy to help patients regain mobility through guided exercises. [SEP] Text: Individualising the users’ exposure could also make the intervention suitable for people who experience side effects of motion sickness and dizziness. In our study, one patient reported feeling dizzy and believed this was due to playing for a long time. Customising the users’ exposure could involve the therapist setting safe playing times to limit these effects so that the system reminds the player to rest in cases where it is more at risk, such as those who suffer motion sickness (Martirosov et al. 2021). Another finding from the combined OT, parent and patient data is that the game successfully reproduced the movements required by the physical rehabilitation therapy and prompted more movement CR. In addition, the game mechanics included many natural interactions, such as grasping, dragging or stretching, to smoothly and precisely replicate the rehabilitation movements safely (Wenk et al. 2021). Therefore, a co-design approach involving designers and physiotherapists and an iterative design process could be an essential aspect of designing this kind of system (Phelan et al. 2021a, b). The qualitative data from the patients, parents and healthcare professionals highlighted that ULMI-IVR rehabilitation therapy for paediatric patients effectively improved motivation and maintained patients’ interest in performing the exercises from home. Furthermore, both the patients and their parents agreed that having the IVR game available increased the likelihood of achieving therapy at home. In our study, this is one of the most salient findings, because although self-directed home-based rehabilitation therapies have many benefits (early rehabilitation, early discharge from a hospital, reduced therapy time and being cost-effective), and they can fail because of the patient’s lack of motivation affecting therapy (Garrett et al. 2014; López-Jaquero, Montero, and Teruel 2019; Piron et al. 2009; Su et al. 2021; Thielbar et al. 2020; Wittmann et al. 2016). Home-based therapy can burden parents with the responsibility of overseeing children’s rehabilitation exercises, especially if children lack motivation. In this study, IVR seemed to reduce this burden: parents did not have to remind their children, and the children were proactive in wanting to exercise with the IVR. It is essential that the children feel motivated and enjoy their activity, as this rehabilitation can be long, repetitive and perceived as painful. Increasing therapeutic adherence is vital to achieving recovery of motor function and avoiding long-term problems. [SEP] Justify:

Output: The text corroborates the claim by detailing how individualized virtual reality (IVR) rehabilitation therapy is used effectively in pediatric patients to encourage movement and engagement in exercises, which aligns with the purpose of helping patients regain mobility. It highlights that the game mechanics replicate the required rehabilitation movements and that patients were motivated to participate in their exercises at home, thus supporting the application of virtual reality in physical therapy.


Input: Task: contrast the claim using the given text. Claim: AI translators will soon eliminate the need for language learning altogether. [SEP] Text: It is important to note that the songs generated by Suno AI are not authentic resources in the context of language learning, though debates are raging in our field about how AI content fits into the concept of authentic materials. We have also found that they sometimes contain culturally or linguistically inaccurate or strange content. Users should exercise caution and may need to modify the content before introducing it into the classroom. for the 1. Educator-Previously, when addressing specific topics in language classes, for example, families, colors, or clothes for novice language learners, educators typically searched for any available online songs and introduced content deemed suitable for classroom instruction. A limitation of these online resources is that language teachers may not have the flexibility to precisely tailor the learning content to meet the lesson objectives or specific p2. Student-Traditionally, students engage with a popular existing song online by learning new words in the lyrics, followed by sentences, rhythms, and melodies through repeated listening to the audio or watching videos. The drawback of this approach lies in the fact that songs available on the internet might not precisely align with the learning objectives, cater to learners’ specific proficiency levels, or resonate with their personal tastes in music genres and vibes. But with the assistance of Suno AI, the possibility for learners to compose a song in a short timeframe is now much more feasible. This creative workflow simplifies the songwriting process, allowing any learner to commence crafting a simple song. They can be provided with choices of sentence starters, specific sentence structures, thematic vocabulary related to the topic of the song, as well as some cultural elements to incorporate into their lyrics such as products, practices, and perspectives. In this way, they will have more guidance in creating their 8-line lyrics in Suno AI while having the freedom to choose based on their own musical p3. Students can share all the Suno AI-generated songs in class and choose the best one. Students can create a title in the target language for the Suno AI generated song. Students can comment on the cover art of the generated song to evaluate if it fits the song or not by writing in the target language. Students can critique the lyrics of the song by discussing which parts do not make sense, which parts can be modified, which parts are their favorite, etc. Students can create ending sentence(s) or modify some of the lyrics based on their own interpretations or their proficiency levels. [SEP] Justify:

Output: The text contrasts the claim by emphasizing that while AI can assist in generating songs and content, it does not serve as an authentic resource for language learning. It mentions the importance of tailoring learning objectives and highlights limitations of AI-generated content in aligning with specific educational needs. This suggests that despite advancements in AI, the need for language learning remains due to the limitations of AI in providing accurate and authentic linguistic experiences.