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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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Topics in Language Disorders
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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.

21 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.
21 works in the cohort · of 4,299,418page 1 of 1

Labels cover 0 of 21 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 21 of 21 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
The Development of Spelling Skill
Rebecca Treiman, Derrick C. Bourassa
2000· article· en· Topics in Language Disorders· Psychology
machine prediction:candidate · noneconsensus · none
241
citations
affunlabeled
Promoting Peer Interaction Skills
Luigi Girolametto, Elaine Weitzman
2007· article· en· Topics in Language Disorders· Psychology
machine prediction:candidate · noneconsensus · none
32
citations
affunlabeled
How Often and How Much?
Allison Breit‐Smith, Laura M. Justice, Anita S. McGinty, Joan N. Kaderavek
2009· article· en· Topics in Language Disorders· Psychology
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
“Well, You Are the One Who Decides”
Jytte Isaksen
2018· article· en· Topics in Language Disorders· Health Professions
machine prediction:candidate · noneconsensus · none
20
citations
affunlabeled
Learning to Read in English and French
Sheila Cira Chung, Poh Wee Koh, S. Hélène Deacon, Xi Chen
2017· article· en· Topics in Language Disorders· Psychology
machine prediction:candidate · noneconsensus · none
18
citations
aboutno affunlabeled
Foreword
Trisha L. Self, Rosalind R. Scudder
2007· article· en· Topics in Language Disorders· Health Professions
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Foreword
Geralyn Timler
2007· article· en· Topics in Language Disorders· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
From the Editor
Nickola Wolf Nelson, Katharine G. Butler
2006· article· en· Topics in Language Disorders· Psychology
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Incidental Word Learning Through Multiple Media
Susan B. Neuman, Tanya Kaefer, Ashley M. Pinkham
2022· article· en· Topics in Language Disorders· Social Sciences
machine prediction:candidate · noneconsensus · none
0
citations

How this was built: Screen · Findings · About