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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.

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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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Global Energy and Sustainability 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.

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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.

2,056 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.
2,056 works in the cohort · of 4,299,418page 14 of 42

Labels cover 5 of 2,056 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 2,056 of 2,056 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.

afffundunlabeled
Microbial solutions must be deployed against climate catastrophe
Raquel S. Peixoto, Christian R. Voolstra, Lisa Y. Stein, Philip Hugenholtz, Joana Falcão Salles, Shady A. Amin +12 more
2024· letter· en· npj Biofilms and Microbiomes· Energy
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Remediation of Sungai Bera Holding Basin, Brunei
Ashok Tandon, Pg. A. Hjh Masnah PAH Ibrahim, D. W. Morehouse, Mike Seymour
2002· article· en· All Days· Energy
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Crude Oil
O. V. Roussak, H. D. Gesser
2012· book-chapter· en· Applied Chemistry· Energy
machine prediction:candidate · noneconsensus · none
1
citations
fundno affunlabeled
Governing Energy Transitions
Kathryn Chelminski
2025· book· en· Cambridge University Press eBooks· Energy
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
The Need for Renewable Energy
R. A. Dunlap
2024· book-chapter· en· Synthesis lectures on renewable energy technologies· Energy
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
The Hibernia Development Project
Qiong Zhang
2013· article· en· The Journal of Macrodynamic Analysis (Memorial University of Newfoundland)· Energy
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
HAITI: A TALE OF TWO DISASTERS
Fernando do Amaral Nogueira
2016· article· pt· Revista de Administração de Empresas· Energy
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
The Iron Grip of Depletion
J. Zagar, C.J. Campbell
2004· article· en· Offshore Technology Conference· Energy
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Harvesting Human Energy
Guillermo Estrada
2020· article· en· Open MIND· Energy
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Canada
2013· book-chapter· en· OECD eBooks· Energy
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Exergy
İbrahim Dinçer
2025· book-chapter· en· Elsevier eBooks· Energy
machine prediction:candidate · noneconsensus · none
1
citations
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