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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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Time Series Analysis and Forecasting
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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.

560 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
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An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
560 works in the cohort · of 4,299,418page 10 of 12

Labels cover 0 of 560 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 560 of 560 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
Automatic classification of time series of patients with chronic pain
Armel Soubeiga, Jessem Ettaghouti, Violaine Antoine, Alice Corteval, Nicolas Kerckhove, Sylvain Moreno
2023· preprint· fr· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
afffundno abstractunlabeled
Clustering discrete-valued time series
Tyler Roick, Dimitris Karlis, Paul D. McNicholas
2020· preprint· en· Advances in Data Analysis and Classification· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affvenueunlabeled
Comparative Approaches to Time-Series Clustering
Ninglee Weng
2025· article· en· Inquiry Queen s Undergraduate Research Conference Proceedings· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Form-Based Semantic Caching on Time Series
Trung-Dung Le, Verena Kantere, Laurent d’Orazio
2024· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Geometrical Realization for Time Series Forecasting
Ali Bayeh, Malek Mouhoub, Samira Sadaoui
2024· book-chapter· en· Communications in computer and information science· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Time Series Models
John H. Maindonald, W. John Braun, Jeffrey L. Andrews
2024· book-chapter· en· Cambridge University Press eBooks· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Amplitude-Invariant Functional Motif Discovery
Jacopo Di Iorio, Marzia A. Cremona, Francesca Chiaromonte
2025· book-chapter· en· Contributions to statistics· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Temporal Analytics
Professor Reda Alhajj, Professor Jon Rokne
2014· book-chapter· en· Computer Science
machine prediction:candidate · noneconsensus · none
0
citations

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