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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 Research
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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.

3,468 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.
3,468 works in the cohort · of 4,299,418page 58 of 70

Labels cover 10 of 3,468 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 3,468 of 3,468 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
Executability of Python Snippets in Stack Overflow
Md Monir Hossain, Nima Mahmoudi, Changyuan Lin, Hamzeh Khazaei, Abram Hindle
2019· preprint· en· arXiv (Cornell University)· Computer Science
machine prediction:candidate · metaresearchconsensus · none
1
citations
affunlabeled
How to do inspections when there is no time
Terry Shepard, Diane Kelly
2001· article· en· International Conference on Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Tool support for working with sets of source code entities
Curtis Fraser, Chris Luce, Jamie Starke, Jonathan Sillito
2008· article· en· Proceedings/Proceedings -- IEEE Symposium on Visual Languages and Human-Centric Computing· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
afffundunlabeled
Towards Generation of Software Development Tasks
C. Albert Thompson
2015· article· en· 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Recovering software requirements from system-user interaction traces
Mohammad El‐Ramly, Eleni Stroulia, Paul Sorenson
2002· article· en· Proceedings of the 14th international conference on Software engineering and knowledge engineering - SEKE '02· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
A comparative exploration of FreeBSD bug lifetimes
Gargi Bougie, Christoph Treude, DM German, MA Storey
2010· article· en· Singapore Management University Institutional Knowledge (InK) (Singapore Management University)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Harmonizing Systems and Software Cost Estimation
Wang Gan, Ricardo Valerdi, John E. Gaffney
2009· article· en· DSpace@MIT (Massachusetts Institute of Technology)· Computer Science
machine prediction:candidate · noneconsensus · none
1
citations

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