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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.

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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.

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 1 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.

fundno affno abstractunlabeled
Experimentation in Software Engineering
Claes Wohlin, Per Runeson, Martin Höst, Magnus C. Ohlsson, Björn Regnell, Anders Wesslén
2000· book· en· Kluwer international series in software engineering· Computer Science
machine prediction:candidate · metaresearchconsensus · none
1,769
citations
affunlabeled
Boundary work in knowledge teams.
Samer Faraj, Aimin Yan
2009· article· en· Journal of Applied Psychology· Computer Science
machine prediction:candidate · stsconsensus · none
305
citations
afffundno abstractunlabeled
Naming the pain in requirements engineering
Stefan Wagner, Marcos Kalinowski, Michael Felderer, Priscilla Mafra, Antonio Vetrò, Tayana Conte +16 more
2016· article· en· Empirical Software Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
271
citations
fundno aff3/3 metaresearchunlabeled
Ethical issues in empirical studies of software engineering
Janice Singer, Norman G. Vinson
2002· article· en· IEEE Transactions on Software Engineering· Computer Science
machine prediction:candidate · metaresearch+research_integrityconsensus · none
190
citations
affunlabeled
The Social Nature of Agile Teams
Elizabeth Whitworth, Robert Biddle
2007· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
178
citations
affunlabeled
Contextualizing agile software development
Philippe Kruchten
2011· article· en· Journal of Software Evolution and Process· Computer Science
machine prediction:candidate · noneconsensus · none
152
citations
affunlabeled
Towards agile security assurance
Konstantin Beznosov, Philippe Kruchten
2005· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
142
citations
affunlabeled
How to read a paper
Srinivasan Keshav
2007· article· en· ACM SIGCOMM Computer Communication Review· Computer Science
machine prediction:candidate · metaresearchconsensus · none
139
citations
affunlabeled
Trade-off Analysis for Requirements Selection
Günther Ruhe, Armin Eberlein, Dietmar Pfahl
2003· article· en· International Journal of Software Engineering and Knowledge Engineering· Computer Science
machine prediction:candidate · noneconsensus · none
114
citations
affunlabeled
Hybrid Intelligence in Software Release Planning
Günther Ruhe, An Ngo The
2004· article· en· International Journal of Hybrid Intelligent Systems· Computer Science
machine prediction:candidate · noneconsensus · none
113
citations
affunlabeled
Status Quo in Requirements Engineering
Stefan Wagner, Daniel Méndez, Michael Felderer, Antonio Vetrò, Marcos Kalinowski, Roel Wieringa +17 more
2019· article· en· ACM Transactions on Software Engineering and Methodology· Computer Science
machine prediction:candidate · noneconsensus · none
112
citations
affno abstractunlabeled
What do software architects really do?
Philippe Kruchten
2008· article· en· Journal of Systems and Software· Computer Science
machine prediction:candidate · stsconsensus · none
107
citations
affunlabeled
The XP Customer Role in Practice: Three Studies
Àngela Martín, Robert Biddle, James Noble
2004· article· en· Agile Development Conference· Computer Science
machine prediction:candidate · noneconsensus · none
93
citations
affno abstractunlabeled
Knowledge Sharing in Agile Software Teams
Thomas Chau, Frank Maurer
2004· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
93
citations

How this was built: Screen · Findings · About