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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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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.

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.

2,056 results · 1 filter active ·
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20002025
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Machine labels · sparse coverage
Evidence
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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 18 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.

aboutno affunlabeled
EISA Section 526: Impacts on DESC Supply
Michael E. Canes, Rachael G Jonassen
2009· article· en· Nature reviews. Neuroscience· Energy
machine prediction:candidate · noneconsensus · none
1
citations
venueno affunlabeled
10.1016/s0967-0653(97)80701-6
C.K. Abernathy
2000· article· en· Time to knit· Energy
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
1
citations
affno abstractunlabeled
Introduction: Differentiation and Uncertainty
Satsuki Kawano, Glenda S. Roberts, Susan Long
2017· book-chapter· en· University of Hawaii Press eBooks· Energy
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
:<i>Climate Change in the Anthropocene</i>
Francine M.G. McCarthy
2024· review· en· The Quarterly Review of Biology· Energy
machine prediction:candidate · noneconsensus · none
0
citations
affaboutunlabeled
The Next Face of Alberta Oilsands
Timothy Artymko
2018· article· en· Student Research Proceedings· Energy
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(95)90453-6
2000· article· en· Time to knit· Energy
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(95)94680-2
2000· article· en· Time to knit· Energy
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Are we running out of oil
Lawrence Martin
2004· article· en· Transport Research Forum· Energy
machine prediction:candidate · noneconsensus · none
0
citations
affvenueno abstractunlabeled
Editorial Remarks
Jennifer Harris
2025· article· en· Canadian Review of American Studies· Energy
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Sustained Global Recovery
Evangelos Otto Simos
2003· article· en· The Journal of Business Forecasting Methods & Systems· Energy
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Workshop Proposal for EPEC 2014
Megan Moore, Fred P. Adams
2014· article· en· Electrical Power and Energy Conference· Energy
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
aboutno affunlabeled
Market Analysis for Petroleum 2020
Franz J. Meyer
2020· article· en· Journal of Industrial Pollution Control· Energy
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affno abstractunlabeled
Operation Osage (Canada, 2006)
2011· book-chapter· en· University of Pennsylvania Press, Inc. eBooks· Energy
machine prediction:candidate · noneconsensus · none
0
citations
venueno affunlabeled
10.70543/10.52305/NUYF7030
2000· book· en· Time to knit· Energy
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(96)86619-1
2000· article· en· Time to knit· Energy
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Non-conventional fossil fuels
R. L. Evans
2012· book-chapter· en· Cambridge University Press eBooks· Energy
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Energy in the History of Technology
Anaël Marrec, Mahdi Khelfaoui
2024· book-chapter· en· Techne.· Energy
machine prediction:candidate · noneconsensus · none
0
citations
affno abstractunlabeled
Biofuel Processing in a Closed-Loop Geothermal System
Alireza Darzi, Mohammad Zargartalebi, Mohammad Amin Kazemi, Mohammad Roostaie, Sepehr Saber, Jason Riordon +4 more
2024· preprint· en· SSRN Electronic Journal· Energy
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Patent Analysis of Oil Sands Technologies
Ki-Bong Lee, Sang‐Goo Jeon, Nam‐Sun Nho, Kwang Ho Kim, Dae-Hyun Shin, Heoung-Yeoun Lee
2009· article· en· Journal of the Korean Institute of Resources Recycling· Energy
machine prediction:candidate · bibliometricsconsensus · none
0
citations
aboutno affunlabeled
Blue sky thinking in energy storage
Myles McCormick
2017· article· en· Industrial Minerals· Energy
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(94)91632-2
2000· article· en· Time to knit· Energy
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About