Evaluation Dataset for RCT Classification by LLMs and Cochrane RCT Classifier

This dataset contains the evaluation results of multiple large language models (LLMs) and the Cochrane RCT classifier in classifying biomedical abstracts as randomized controlled trials (RCTs) or non-RCTs. The dataset was constructed by retrieving 2,252 articles related to "Thrombectomy" from PubMed, then manually labeled by two independent reviewers to establish a gold standard. Six LLMs (5 foundational LLMs, 1 fine-tuned LLMs) were then prompted to classify the same set of abstracts using a consistent instruction template. The Cochrane RCT classifier output is included for benchmarking. Each model’s binary decision (“Include” for probable RCT; “Exclude” otherwise) and a brief justification are recorded.

Column Definitions:

Title: Title of the article.

Abstract: Abstract of the article.

Gold_Standard: Manual label assigned by consensus review (1 = RCT, 0 = non-RCT).

Cochrane_decision: Output from the Cochrane RCT classifier (1 = probable RCT, 0 = not RCT).

GPT_4.1_decision: Output from the GPT-4.1 model (1 = Include, 0 = Exclude).

Reason: Brief justification from the GPT-4.1 model.

Llama_4_Maverick_decision: Output from the Llama-4-Maverick model (1 = Include, 0 = Exclude).

Reason: Brief justification from the Llama-4-Maverick model.

R1_Distilled_Qwen_32B_decision: Output from the R1 Distilled Qwen-32B model (1 = Include, 0 = Exclude).

Reason: Brief justification from the Qwen-32B model.

Qwen3_14B_decision: Output from the Qwen3-14B model (1 = Include, 0 = Exclude).

Reason: Brief justification from the Qwen3-14B model.

Mistral_Nemo_Instruct_2407_decision: Output from the pre-fine-tuned Mistral model (1 = Include, 0 = Exclude).

Reason: Brief justification from the pre-fine-tuned Mistral model.

Fine_tuned_Mistral_Nemo_Instruct_2407_decision: Output from the fine-tuned Mistral model (1 = Include, 0 = Exclude).

Reason: Brief justification from the fine-tuned Mistral model.