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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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Experimental Learning in Engineering
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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
fundfunder
venuejournal
aboutaboutness

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

892 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.
892 works in the cohort · of 4,299,418page 15 of 18

Labels cover 1 of 892 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 892 of 892 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

affunlabeled
Development of Attachments for the Quanser Qube
Diane Peters, Aaron-Joseph Jones
2024· article· en· 2021 ASEE Virtual Annual Conference Content Access Proceedings· Engineering
distilled prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
Design of an Online Digital Filtering Laboratory
Ulrich Borgolte, Clemens Zang
2011· article· en· Technology for Education and Learning· Engineering
distilled prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Scripting and Orchestration in Smart Classrooms.
Michael Benjamin Tissenbaum
2013· article· en· Computer Supported Collaborative Learning· Engineering
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations
affunlabeled
Robotics in Electronics Engineering Technology
Asad Yousuf, Mohamad Mustafa, Alberto De La Cruz, Alfredo Villanueva, Mir Hayder
2020· article· en· Engineering
distilled prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
IOLTS 2022 Foreword
2022· article· en· Engineering
distilled prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Trends*
2015· article· en· Engineering
distilled prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Transport Phenomena Teaching
Pierre Proulx, Francis B. Lavoie
2019· article· en· Engineering
distilled prediction:candidate · noneconsensus · none
0
citations
fundno affno abstractunlabeled
CHALLENGE FOR THE SUBJECTIVE EXPERIMENT USING HEADPHONE
Susumu Hirakawa, Hiroaki Sato, Manabu Chikai, Ayako Hiramatsu, H SATI, Jeffrey Mahn +1 more
2023· article· Engineering
distilled prediction:candidate · metaepi_narrowconsensus · none
0
citations

How this was built: Screen · Findings · About