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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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Software Engineering Techniques and Practices
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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.

1,138 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.
1,138 works in the cohort · of 4,299,418page 5 of 23

Labels cover 1 of 1,138 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 1,138 of 1,138 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.

affunlabeled
COMPARISON OF OPEN SOURCE TOOLS FOR PROJECT MANAGEMENT
André Marques Pereira, Rafael Queiroz Gonçalves, Christiane Gresse von Wangenheim, Luigi Buglione
2013· article· en· International Journal of Software Engineering and Knowledge Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
23
citations
venueno affunlabeled
Planning for Integrating Teaching Technologies
Mandie Aaron, D. R. Dicks, Cindy Ives, Brenda Montgomery
2004· article· en· Canadian Journal of Learning and Technology· Computer Science
machine prediction:candidate · noneconsensus · none
23
citations
affunlabeled
DrProject
Karen Reid, Greg Wilson
2007· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
23
citations
affno abstractunlabeled
A Repository of Agile Method Fragments
Hesam Chiniforooshan Esfahani, Eric Yu
2010· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
22
citations
affno abstractunlabeled
Software Engineering as Cooperative Work
Yvonne Dittrich, D.W. Randall, Janice Singer
2009· article· en· Computer Supported Cooperative Work (CSCW)· Computer Science
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Agile methods
Frank Maurer, Grigori Melnik
2006· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Fuzzy-ExCOM Software Project Risk Assessment
Ekananta Manalif, Luiz Fernando Capretz, Ali Bou Nassif, Danny Ho
2012· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
19
citations
affno abstractunlabeled
Software Systems Engineering programmes a capability approach
Carl E. Landwehr, Jochen Ludewig, Robert Meersman, David Lorge Parnas, Peretz Shoval, Yair Wand +2 more
2016· article· en· Journal of Systems and Software· Computer Science
machine prediction:candidate · noneconsensus · none
19
citations
affunlabeled
ClassCompass
Wesley Coelho, Gail C. Murphy
2007· article· en· Journal on Educational Resources in Computing· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
18
citations
affunlabeled
Evaluating Student Teams
Anya Tafliovich, Andrew Petersen, Jennifer Campbell
2016· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
18
citations
aboutno affunlabeled
From software requirements to architectures
Jaelson Castro, Jeff Kramer
2001· article· en· International Conference on Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
18
citations
affunlabeled
Agility in context
Rashina Hoda, Philippe Kruchten, James Noble, Stuart Marshall
2010· article· en· ACM SIGPLAN Notices· Computer Science
machine prediction:candidate · noneconsensus · none
18
citations
affno abstractunlabeled
A Digital Game Maturity Model (DGMM)
2016· article· en· Entertainment Computing· Computer Science
machine prediction:candidate · noneconsensus · none
17
citations

How this was built: Screen · Findings · About