Dataset
clinical-trials-trec-qrels
clinical-trials-trec-qrels is a tabular relevance-judgment file distributed by the 2001jdev user on the Hugging Face Hub. It maps clinical-trial topic identifiers to NCT registry IDs with graded relevance scores.
Data preview
Dataset card
What this dataset contains
The file pairs numeric topic identifiers with National Clinical Trial (NCT) identifiers, recording whether each trial is considered relevant to the topic. A year field tags every row, and the dataset is split across 2021, 2022 and 2023 with a combined 105,096 rows, putting it in the 100K–1M size band. License, publisher provenance and underlying source corpus are not declared in the supplied metadata.
Structure and fields
Four columns make up the schema: topic_id (int64), nct_id (string), relevance (int64) and year (int64). Rows are stored in Parquet format and can be loaded with the datasets, pandas or polars libraries, or accessed through the mlcroissant metadata. There is no free-text column; each row is a flat judgment linking one topic to one NCT record for a single year.
How analysts use it
Researchers evaluating clinical-trial search and retrieval systems can use the qrels to measure how well an information-retrieval model surfaces relevant trials per topic_id. The nct_id column enables joins against registry metadata, while relevance and year support year-over-year comparisons of judgment sets. Because licensing is unstated, commercial redistribution should be confirmed before any production use.
Documentation & references 1
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