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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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Gaze Tracking and Assistive Technology
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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
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

688 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.
688 works in the cohort · of 4,299,418page 1 of 14

Labels cover 0 of 688 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 688 of 688 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
GAZE-2
Roel Vertegaal, Ivo Weevers, Changuk Sohn, Chris Cheung
2003· article· en· Computer Science
machine prediction:candidate · insufficient_payloadconsensus · none
214
citations
affunlabeled
The eyes don't have it
Yuan Yuan Qian, Robert J. Teather
2017· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
164
citations
affno abstractunlabeled
A comparison of scanpath comparison methods
Nicola Anderson, Fraser Anderson, Alan Kingstone, Walter F. Bischof
2014· article· en· Behavior Research Methods· Computer Science
machine prediction:candidate · noneconsensus · none
164
citations
afffundno abstractunlabeled
Evaluating Eye Tracking with ISO 9241 - Part 9
Xuan Zhang, I. Scott MacKenzie
2007· book-chapter· en· Lecture notes in computer science· Computer Science
machine prediction:candidate · noneconsensus · none
134
citations
affunlabeled
Efficient eye pointing with a fisheye lens
Michael Ashmore, Andrew T. Duchowski, Garth Shoemaker
2005· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
107
citations
affunlabeled
EyeWindows
David Fono, Roel Vertegaal
2005· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
99
citations
affunlabeled
The use of gaze to control drones
John Paulin Hansen, Alexandre Alapetite, I. Scott MacKenzie, Emilie Møllenbach
2014· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
97
citations
fundno affunlabeled
BubbleView
2017· article· en· ACM Transactions on Computer-Human Interaction· Computer Science
machine prediction:candidate · noneconsensus · none
84
citations
affunlabeled
Implanted user interfaces
Christian Holz, Tovi Grossman, George Fitzmaurice, Anne Agur
2012· article· en· Computer Science
machine prediction:candidate · noneconsensus · none
75
citations
affno abstractunlabeled
BlinkWrite: efficient text entry using eye blinks
I. Scott MacKenzie, Behrooz Ashtiani
2010· article· en· Universal Access in the Information Society· Computer Science
machine prediction:candidate · noneconsensus · none
72
citations
affunlabeled
Interacting with groups of computers
Jeffrey S. Shell, Ted Selker, Roel Vertegaal
2003· article· en· Communications of the ACM· Computer Science
machine prediction:candidate · noneconsensus · none
68
citations

How this was built: Screen · Findings · About