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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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Springer series in the data sciences
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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.

12 results · 1 filter active ·
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20152022
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
12 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 12 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 12 of 12 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Lectures on the Nearest Neighbor Method
2015· book· en· Springer series in the data sciences· Computer Science
distilled prediction:candidate · scholarly_communication+open_scienceconsensus · none
224
citations
affno abstractunlabeled
The nearest neighbor distance
2015· book-chapter· en· Springer series in the data sciences· Computer Science
distilled prediction:candidate · scholarly_communication+open_scienceconsensus · none
1
citations
affno abstractunlabeled
Multivariate Methods
2022· book-chapter· en· Springer series in the data sciences· Mathematics
distilled prediction:candidate · insufficient_payloadconsensus · none
1
citations
affno abstractunlabeled
Symbolic Data Analysis
2022· book-chapter· en· Springer series in the data sciences· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+open_science+insufficient_payloadconsensus · open_science
1
citations
affno abstractunlabeled
The choice of a nearest neighbor estimate
2015· book-chapter· en· Springer series in the data sciences· Computer Science
distilled prediction:candidate · open_scienceconsensus · none
0
citations
affno abstractunlabeled
Order statistics and nearest neighbors
2015· book-chapter· en· Springer series in the data sciences· Computer Science
distilled prediction:candidate · open_scienceconsensus · none
0
citations
affno abstractunlabeled
Multiple Change-Point Problems
2018· book-chapter· en· Springer series in the data sciences· Mathematics
distilled prediction:candidate · insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Bayesian Computation Methods
2022· book-chapter· en· Springer series in the data sciences· Computer Science
distilled prediction:candidate · open_scienceconsensus · none
0
citations
affno abstractunlabeled
Efficiency
2018· book-chapter· en· Springer series in the data sciences· Mathematics
distilled prediction:candidate · metaresearch+sts+open_science+insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Regression: the noiseless case
2015· book-chapter· en· Springer series in the data sciences· Mathematics
distilled prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
One-Sample and Two-Sample Problems
2018· book-chapter· en· Springer series in the data sciences· Mathematics
distilled prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About