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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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Explainable Artificial Intelligence (XAI)
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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.

675 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.
675 works in the cohort · of 4,299,418page 12 of 14

Labels cover 1 of 675 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 675 of 675 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Communicating Uncertainty Can Increase AI Adoption
Mohsen Foroughifar, Rozhina Ghanavi, Avi Goldfarb, Ryan Webb
2025· preprint· en· SSRN Electronic Journal· Computer Science
distilled prediction:candidate · metaepi_narrow+research_integrityconsensus · none
0
citations
affunlabeled
A Trustworthy View on XAI Method Evaluation
DING LI, Yan Liu, Zerui Wang
2022· preprint· en· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Responsible Agentic Reasoning and AI Agents: A Critical Survey
Shaina Raza, Ranjan Sapkota, Manoj Karkee, Christos Emmanouilidis
2025· preprint· Computer Science
distilled prediction:candidate · metaresearch+metaepi_narrow+scholarly_communication+open_science+insufficient_payloadconsensus · none
0
citations
affunlabeled
Strategic Foundation Models
Denizalp Goktas, Amy Greenwald, Takayuki Osogami, Roma Patel, Kevin Leyton‐Brown, Grant Schoenebeck +19 more
2025· preprint· en· HAL (Le Centre pour la Communication Scientifique Directe)· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
0
citations
aboutno affunlabeled
La Fiesta de Los Angeles float, 1915
2012· dataset· en· University of Southern California Digital Library· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Kantian-Utilitarian XAI: Meta-Explained
Zahra Atf
2025· article· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communication+insufficient_payloadconsensus · insufficient_payload
0
citations
fundno affunlabeled
MIB: A Mechanistic Interpretability Benchmark
Aaron Mueller, Atticus Geiger, Sarah Wiegreffe, Dana Arad, Iván Arcuschin, Adam Belfki +15 more
2025· preprint· en· UvA-DARE (University of Amsterdam)· Computer Science
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
fundno affunlabeled
Learning Explanations from Language Data
David Harbecke, Robert Schwarzenberg, Christoph Alt
2018· preprint· en· Computer Science
distilled prediction:candidate · open_science+insufficient_payloadconsensus · open_science
0
citations
affunlabeled
Model AI Assignments 2022
Todd W. Neller, Jazmin Collins, Daniel Schneider, Yim Register, Christopher Brooks, Tang, Chiawei +7 more
2022· article· en· Computer Science
distilled prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Occurrence Download
2023· dataset· en· Global Biodiversity Information Facility· Computer Science
distilled prediction:candidate · metaepi_narrow+insufficient_payloadconsensus · none
0
citations
affno abstractunlabeled
Traffic Crash Severity Prediction Using eXplainable AI
Nishtha Srivastava, Rishabh Maloo, Bhavesh N. Gohil, Suprio Ray
2025· book-chapter· en· Communications in computer and information science· Computer Science
distilled prediction:candidate · metaepi_narrow+scholarly_communicationconsensus · none
0
citations

How this was built: Screen · Findings · About