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JerMa88/TPR_Peer_Reviews

Transparent Peer Review (TPR) Dataset This dataset contains peer reviews from TPR, standardized to match the format of the pawin205/PeerRT dataset. Dataset Structure Each record contains the following attributes: relative_rank: Default value (0). win_prob: Default value (0.0). title: Title of the paper. abstract: Abstract of the paper. full_text: Full text of the paper (or review text if unavailable). review: The peer review text. source: Source of the data… See the full description on the dataset page: https://huggingface.co/datasets/JerMa88/TPR_Peer_Reviews.

sourceHugging Facecc-by-4.0updated 10mo agoView on Hugging Face
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Dataset Card

Transparent Peer Review (TPR) Dataset

This dataset contains peer reviews from TPR, standardized to match the format of the pawin205/PeerRT dataset.

Dataset Description

  • —Source: TPR
  • —Standardization: Matches pawin205/PeerRT schema with an additional year attribute.
  • —Total Records: (See dataset viewer)

Dataset Structure

Each record contains the following attributes:

  • —relative_rank: Default value (0).
  • —win_prob: Default value (0.0).
  • —title: Title of the paper.
  • —abstract: Abstract of the paper.
  • —full_text: Full text of the paper (or review text if unavailable).
  • —review: The peer review text.
  • —source: Source of the data ('TPR').
  • —review_src: Original filename of the review.
  • —criteria_count: Dictionary containing counts of specific criteria in the review (e.g., criticism, praise).
  • —dimension_scores: Dictionary containing scores for various dimensions.
  • —overall_score: Computed overall score (reward value).
  • —thinking_trace: Placeholder (empty).
  • —prompt: Placeholder (empty).
  • —prompt_length: Placeholder (0).
  • —conversations: List of dictionaries representing the conversation (User/Assistant format).
  • —year: Year of publication (if available).

Usage

python
from datasets import load_dataset

dataset = load_dataset("JerMa88/TPR_Peer_Reviews")
print(dataset['train'][0])