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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.

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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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Advanced Statistical Process Monitoring
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.

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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.

431 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.
431 works in the cohort · of 4,299,418page 1 of 9

Labels cover 1 of 431 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 431 of 431 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
On-line outlier detection and data cleaning
Hancong Liu, Sirish L. Shah, Wei Jiang
2004· article· en· Computers & Chemical Engineering· Decision Sciences
machine prediction:candidate · noneconsensus · none
431
citations
affno abstractunlabeled
A Bibliography of Process Capability Papers
Fred Spiring, Bartholomew P.K. Leung, Smiley W. Cheng, Anthony Yeung
2003· article· en· Quality and Reliability Engineering International· Decision Sciences
machine prediction:candidate · bibliometricsconsensus · none
153
citations
affno abstractunlabeled
A new nonparametric EWMA Sign Control Chart
Su‐Fen Yang, Jheng-Sian Lin, Smiley W. Cheng
2010· article· en· Expert Systems with Applications· Decision Sciences
machine prediction:candidate · noneconsensus · none
136
citations
venueno affunlabeled
Set estimation and nonparametric detection
Amparo Ba ÍLLO, Antonio Cuevas, Ana Justel
2000· article· en· Canadian Journal of Statistics· Decision Sciences
machine prediction:candidate · noneconsensus · none
79
citations
afffundunlabeled
Monitoring Processes with Highly Censored Data
Stefan H. Steiner, Robert J. MacKay
2000· article· en· Journal of Quality Technology· Decision Sciences
machine prediction:candidate · noneconsensus · none
77
citations
affunlabeled
A new non‐parametric CUSUM mean chart
Su‐Fen Yang, Smiley W. Cheng
2010· article· en· Quality and Reliability Engineering International· Decision Sciences
machine prediction:candidate · noneconsensus · none
74
citations
affunlabeled
A CCC‐<i>r</i> chart for high‐yield processes
Hiroshi Ohta, Etsuko Kusukawa, Abdur Rahim
2001· article· en· Quality and Reliability Engineering International· Decision Sciences
machine prediction:candidate · noneconsensus · none
60
citations
afffundno abstractunlabeled
Economic and economic statistical designs of the synthetic <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si3.gif" overflow="scroll"><mml:mrow><mml:mover accent="true"><mml:mrow><mml:mi>X</mml:mi></mml:mrow><mml:mrow><mml:mo stretchy="true">¯</mml:mo></mml:mrow></mml:mover></mml:mrow></mml:math> chart using loss functions
Wai Chung Yeong, Michael B. C. Khoo, Ming Ha Lee, M. A. Rahim
2013· article· lv· European Journal of Operational Research· Decision Sciences
machine prediction:candidate · noneconsensus · none
50
citations
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