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## Disclaimer
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This tool is developed to analyze and predict the prevalence of positive and negative results in scientific abstracts based on the SciBERT model. While publication bias is a plausible explanation for certain patterns of results observed in scientific literature, the analyses conducted by this tool do not conclusively establish the presence of publication bias or any other underlying factors. It's essential to understand that this tool evaluates data but does not delve into the underlying reasons for the observed trends.
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**Figure 1** <br>
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*Comparing model performances across in-domain and out-of-domain data; Colored bars represent different model types; Samples: `MAIN` test: n = 198 abstracts; `VAL1`: n = 150 abstracts; `VAL2`: n = 150 abstracts.*
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<br>
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## Disclaimer
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This tool is developed to analyze and predict the prevalence of positive and negative results in scientific abstracts based on the SciBERT model. While publication bias is a plausible explanation for certain patterns of results observed in scientific literature, the analyses conducted by this tool do not conclusively establish the presence of publication bias or any other underlying factors. It's essential to understand that this tool evaluates data but does not delve into the underlying reasons for the observed trends.
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