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4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

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Lung Cancer Diagnosis and Treatment
Retraction
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Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
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The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

2,572 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
2,572 works in the cohort · of 4,299,418page 42 of 52

Labels cover 12 of 2,572 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 2,572 of 2,572 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Response to the Letters to the Editor by Jing Peng and Colleagues and by Lauren C Leiman Regarding the Manuscript “Terminology Issues in Screening and Early Detection of Lung Cancer—International Association for the Study of Lung Cancer Early Detection and Screening Committee Expert Group Recommendations”
Rudolf M. Huber, Stephen Lam, Milena Čavić, Haval Balata, Andrea Borondy Kitts, John K. Field +7 more
2025· letter· en· Journal of Thoracic Oncology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
N2 is not N2 is not N2
Waël C. Hanna
2015· letter· en· Journal of Thoracic and Cardiovascular Surgery· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Welcome to the Era of the Nodule
Waël C. Hanna
2017· letter· en· Seminars in Thoracic and Cardiovascular Surgery· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
In Response to Grégoire et al
Mark T. Corkum, David A. Palma
2020· article· en· Advances in Radiation Oncology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Invited Commentary
Sudhir Sundaresan
2015· letter· en· The Annals of Thoracic Surgery· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
O-030 * THE BURDEN OF DEATH FOLLOWING DISCHARGE AFTER LOBECTOMY
Laura Schneider, Forough Farrokhyar, Adam Bassili, Yaron Shargall, Colin Schieman, Waël C. Hanna +1 more
2014· article· en· Interactive Cardiovascular and Thoracic Surgery· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Are We There Yet?
Anne V. Gonzalez, Lonny Yarmus
2025· editorial· en· CHEST Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Rebuttal from Prof. Rodrigues
George Rodrigues
2016· article· en· Translational Lung Cancer Research· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
In Reply to Burton and Hardcastle
Dawn Owen, Joseph K. Salama, Megan E. Daly, Tim J. Kruser, Meredith Giuliani
2024· letter· en· International Journal of Radiation Oncology*Biology*Physics· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
The Dawn of the Age of Virtual Biopsies
Waël C. Hanna
2019· letter· en· Seminars in Thoracic and Cardiovascular Surgery· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Clinical Utility of Flexible 19G EBUS-TBNA Needle
Tomonari Kinoshita, Hideki Ujiie, Kosuke Fujino, Hitoshi Igai, Christina McDonald, Changyoung Lee +4 more
2017· article· en· CHEST Journal· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Case 46
C. Isabela S. Silva, Néstor L. Müller
2010· book-chapter· en· Elsevier eBooks· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/j.ymed.2014.08.026
2000· article· en· Time to knit· Medicine
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affno abstractunlabeled
Invited commentary
Marc de Perrot
2004· article· en· The Annals of Thoracic Surgery· Medicine
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
In Reply to Cihoric and Jeremic
B. C. John Cho
2015· letter· en· International Journal of Radiation Oncology*Biology*Physics· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
In Reply to Cobben and Jager
George Rodrigues, Suresh Senan, David A. Palma
2015· letter· en· International Journal of Radiation Oncology*Biology*Physics· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
In response to Drs. Vordermark and Kölbl
Luís Souhami, Ervin B. Podgoršak, Minesh P. Mehta, David Brachman, Maria Werner‐Wasik, Walter J. Curran +6 more
2005· article· en· International Journal of Radiation Oncology*Biology*Physics· Medicine
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
In Reply to Chang and Liu
Daniel Moore-Palhares, Hanbo Chen, Ezra Hahn, Justin Lee, Danny Vesprini
2024· letter· en· Practical Radiation Oncology· Medicine
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About