id,statement,domain,status,falsify,novelty_vs_graph,about_lom_id,quote,quote_locus,created_ts
ts-claim-c1-scifact-no-global-truth,"Given a fixed scientific corpus, a claim is not assigned a global truth label; verification is a SUPPORTS / REFUTES / NOINFO relation on each claim–abstract pair, because a global label would require systematic review.",CS / NLP / metascience,proposed,"If a later primary methods paper shows a single corpus-level truth bit can be assigned without systematic review and still match a team-of-experts systematic-review verdict at high agreement on SciFact-style claims, then Wadden et al.’s §2 reason for refusing a global label does not hold.","Literature-grounded restatement of SciFact’s task definition vs ingested paper doi:10.18653/v1/2020.emnlp-main.609, not a model-invented title.",doi:10.18653/v1/2020.emnlp-main.609,"While SCIFACT claims are indeed verifiable assertions about scientific findings, accurately assigning a global truth label to a scientific claim (given a fixed scientific corpus) requires a systematic review by a team of experts. In this work we focus on the simpler task of assigning SUPPORTS or REFUTES relations to individual claim-abstract pairs.",Wadden et al. 2020 §2 PDF (Anthology 2020.emnlp-main.609.pdf),2026-09-01T22:28:39Z
ts-claim-c2-scifact-mixed-polarity,"SciFact’s task definition allows one claim to be both supported and refuted by different abstracts; the authors report that mix on real COVID-19 system outputs (Table 1, §6.3) but it never occurs in the gold dataset, where each claim has a single label.",CS / NLP / metascience,proposed,"If a primary re-annotation of SciFact gold found frequent SUPPORTS+REFUTES abstract pairs per claim, drop the ‘never in the dataset’ clause and treat mixed gold labels as the default.",Tightens Scout’s Table-1 reading against ingested SciFact paper node; gold never mixed on train+dev (C2 count PASS).,doi:10.18653/v1/2020.emnlp-main.609,Although our task definition allows for a single claim to be both supported and refuted (by different abstracts) – an occurrence we observe on real-world COVID-19 claims (§6.3) – this never occurs in our dataset. Each claim has a single label.,Wadden et al. 2020 §3.3 PDF,2026-09-01T22:28:39Z