Aspirin plus clopidogrel was not linked to risk for cancer compared with aspirin alone or no antiplatelets
Bibliographic record
Abstract
ACP Journal Club18 July 2017Aspirin plus clopidogrel was not linked to risk for cancer compared with aspirin alone or no antiplateletsMitchell Levine, MDMitchell Levine, MDMcMaster University, Hamilton, Ontario, Canada (M.L.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/ACPJC-2017-167-2-010 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Source CitationLeader A, Zelikson-Saporta R, Pereg D, et al. The effect of combined aspirin and clopidogrel treatment on cancer incidence. Am J Med. 2017 Feb 14. [Epub ahead of print]. https://pubmed.ncbi.nlm.nih.gov/28213047Clinical Impact RatingsGIM/FP/GP: Cardiology: Oncology: Reference1 Serebruany VL1, Cherepanov V, Cabrera-Fuentes HA, Kim MH. Solid cancers after antiplatelet therapy: Confirmations, controversies, and challenges. Thromb Haemost. 2015;114:1104-12. [PMID: 26559427] Google Scholar Author, Article, and Disclosure InformationAffiliations: McMaster University, Hamilton, Ontario, Canada (M.L.)This article was published at Annals.org on 4 July 2017. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics Cited byCYP2C19 and ABCB1 genetic polymorphisms correlate with the recurrence of ischemic cardiovascular adverse events after clopidogrel treatment 18 July 2017Volume 167, Issue 2Page: JC10KeywordsAntiplatelet therapyAspirinBody mass indexCancer detection and diagnosisCancer treatmentCohort studiesDrugsHealth maintenance organizationsMedical servicesMelanoma ePublished: 18 July 2017 Issue Published: 18 July 2017 Copyright & PermissionsCopyright © 2017 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".