Fliar BI / Research

Tracing and Filtering Unsupported Biomedical Extractions in a 55.5-Million-Relation Corpus

Narendra Kumar · Fliar BI · Preprint v2 · 15 September 2026
Not peer reviewed. arXiv submission has not been completed.

Read the research

What the experiments found

We recovered archived extractor inputs for 1,012 of 1,030 sampled documents. In the new temporal holdout, 299 recovered inputs contain none of the tested COVID-family terms, yet their released outputs include 380 explicit COVID-family rows. A fixed lexical rejection rule withholds all 380.

A retained-checkpoint replay matches the full released tuples for 62 of 70 new documents. The same model generates 51 COVID-family rows from 30 temporal inputs; all fail the proposed safeguard. In the general sample strata, the safeguard retains 77.2–86.3% of rows. These are measured computational outcomes, not clinical accuracy estimates.

Literal-entity filter retention: 3.3 percent in temporal holdout, 80 percent in COVID comparison, and 77.2 to 86.3 percent across general strata, with conditional bootstrap intervals.
Row retention among recovered inputs. Intervals resample documents within each stratum. Missing inputs and sampling limitations are documented in the paper.

Inspect the sample data

These are stratified experimental samples, not population-proportional samples or a replacement HCC release. Literal entity support does not establish a true or even textually entailed relationship. Independent human semantic validation remains outstanding.

Data and reproducibility

The audited HCC v1.0 data are archived on Zenodo and Figshare. Original release files are unchanged. Code, sampled decisions, input fingerprints, replay outputs and aggregate results are available here. Full historical input passages and model weights are not redistributed, limiting independent regeneration of the added replay experiments.