Updating README
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README.md
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@@ -29,19 +29,4 @@ by [Gabriel Okasa](https://orcid.org/0000-0002-3573-7227),
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[Stefan Müller](https://orcid.org/0000-0002-6315-4125), available on arXiv: https://arxiv.org/abs/2411.16662 .
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The fine-tuning codes are open-sourced on GitHub: https://github.com/snsf-data/ml-peer-review-analysis .
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The fine-
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- `snsf-data/specter2-review-track-record`: *Does the sentence address the scientific qualifications of the applicant(s)/team?*
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- `snsf-data/specter2-review-relevance-originality-topicality`: *Does the sentence address the scientific relevance/impact/originality of the proposed research project?*
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- `snsf-data/specter2-review-suitability`: *Does the sentence address the suitability of the methods to be used within the proposed research project?*
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- `snsf-data/specter2-review-feasibility`: *Does the sentence address the feasibility of the proposed research project?*
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- `snsf-data/specter2-review-applicant`: *Does the sentence address the applicant(s)/team or their qualifications, without mentioning quantitative indicators?*
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- `snsf-data/specter2-review-applicant-quantity`: *Does the sentence use quantitative indicators to describe the applicant(s)or team?*
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- `snsf-data/specter2-review-proposal`: *Does the sentence address the proposal or specific parts of it, as opposed to the applicant(s) or context beyond the proposal (such as the research field or the funding scheme’s objectives etc.)?*
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- `snsf-data/specter2-review-method`: *Does the sentence address the methods to be used in the proposed research project?*
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- `snsf-data/specter2-review-positive`: *Is the sentence itself a positive statement or does it contain a positive statement?*
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- `snsf-data/specter2-review-negative`: *Is the sentence itself a negative statement or does it contain a negative statement?*
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- `snsf-data/specter2-review-suggestion`: *Does the sentence suggest how to improve the proposal?*
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- `snsf-data/specter2-review-rationale`: *Does the sentence provide rationale supporting the positive or negative statement?*
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The model cards provide further details on the fine-tuning procedure and evaluation metrics as well as minimal examples for usage of the models.
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[Stefan Müller](https://orcid.org/0000-0002-6315-4125), available on arXiv: https://arxiv.org/abs/2411.16662 .
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The fine-tuning codes are open-sourced on GitHub: https://github.com/snsf-data/ml-peer-review-analysis .
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The model cards provide further details on the models, the fine-tuning procedure and evaluation metrics as well as minimal examples for usage of the models.
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