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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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Trends in Cognitive Sciences
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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.

257 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.
257 works in the cohort · of 4,299,418page 5 of 6

Labels cover 1 of 257 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 257 of 257 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.

afffundno abstractunlabeled
New strategies for the cognitive science of dreaming
Remington Mallett, Karen Konkoly, Toré Nielsen, Michelle Carr, Ken A. Paller
2024· review· en· Trends in Cognitive Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
10
citations
affno abstractunlabeled
A timeline of cognitive costs in decision-making
Christin Schulze, Ada Aka, Daniel M. Bartels, Stefan Bucher, Jake Ryan Embrey, Todd M. Gureckis +9 more
2025· review· en· Trends in Cognitive Sciences· Decision Sciences
machine prediction:candidate · noneconsensus · none
10
citations
afffundno abstractunlabeled
Identifying indicators of consciousness in AI systems
Patrick Butlin, Robert P. Long, Tim Bayne, Yoshua Bengio, Jonathan Birch, David J. Chalmers +14 more
2025· review· en· Trends in Cognitive Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
8
citations
affno abstractunlabeled
Could Brain Decoding Machines Change Our Minds?
Vincent Taschereau‐Dumouchel, Mathieu Roy
2020· review· en· Trends in Cognitive Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Show us the model
Mark S. Seidenberg, Marc F. Joanisse
2003· review· en· Trends in Cognitive Sciences· Computer Science
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Comparing cognition across species
Simon M. Reader, Daniel Sol, Louis Lefebvre
2005· review· en· Trends in Cognitive Sciences· Psychology
machine prediction:candidate · noneconsensus · none
7
citations
affno abstractunlabeled
Why is cognitive effort experienced as costly?
A. Ross Otto, Andrew Westbrook, Jean Daunizeau
2025· article· en· Trends in Cognitive Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
6
citations
affno abstractunlabeled
If You Become Evil, Do You Die?
Christina Starmans, Paul Bloom
2018· review· en· Trends in Cognitive Sciences· Psychology
machine prediction:candidate · noneconsensus · none
6
citations
fundno affno abstractunlabeled
The ubiquity of episodic-like memory during infancy
Lillian Behm, Nicholas B. Turk‐Browne, Melissa M. Kibbe
2025· review· en· Trends in Cognitive Sciences· Psychology
machine prediction:candidate · noneconsensus · none
5
citations
affno abstractunlabeled
Clarifying the self: Response to Northoff
Kalina Christoff, Diego Cosmelli, Dorothée Legrand, Evan Thompson
2011· review· en· Trends in Cognitive Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
4
citations
afffundno abstractunlabeled
And yet, the hippocampus codes conjunctively
Luca D. Kolibius, Sheena A. Josselyn, Simon Hanslmayr
2025· review· en· Trends in Cognitive Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
4
citations
afffundno abstractunlabeled
Animals and the iterative natural kind strategy
Tim Bayne, Anil Seth, Marcello Massimini, Joshua Shepherd, Axel Cleeremans, Stephen M. Fleming +7 more
2024· review· en· Trends in Cognitive Sciences· Arts and Humanities
machine prediction:candidate · stsconsensus · none
4
citations
affno abstractunlabeled
What competition?
James T. Enns, Vincent Di Lollo
2002· review· en· Trends in Cognitive Sciences· Neuroscience
machine prediction:candidate · noneconsensus · none
3
citations
fundno affno abstractunlabeled
Anxiety involves altered planning
Paul B. Sharp
2024· review· en· Trends in Cognitive Sciences· Psychology
machine prediction:candidate · noneconsensus · none
3
citations
affno abstractunlabeled
The nature of the memetic beast
Simon M. Reader
2001· review· en· Trends in Cognitive Sciences· Social Sciences
machine prediction:candidate · noneconsensus · none
2
citations
fundno affno abstractunlabeled
How does the quality space come to be?
Krzysztof Dołęga, Inès Mentec, Axel Cleeremans
2024· review· en· Trends in Cognitive Sciences· Psychology
machine prediction:candidate · noneconsensus · none
1
citations
affno abstractunlabeled
Environments for fast and slow thinking
Keith E. Stanovich
2012· review· en· Trends in Cognitive Sciences· Decision Sciences
machine prediction:candidate · noneconsensus · none
1
citations
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