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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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New Phytologist
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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.

972 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.
972 works in the cohort · of 4,299,418page 19 of 20

Labels cover 0 of 972 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 972 of 972 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.

affaboutunlabeled
Whither plant evo‐devo?
William E. Friedman, Spencer C. H. Barrett, Pamela K. Diggle, Vivian F. Irish, Larry Hufford
2008· article· en· New Phytologist· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
4
citations
affaboutunlabeled
Bringing trees into the fuel line
Brian E. Ellis
2012· article· en· New Phytologist· Engineering
machine prediction:candidate · noneconsensus · none
3
citations
afffundunlabeled
Measuring natural selection on the transcriptome
John R. Stinchcombe, John K. Kelly
2025· review· en· New Phytologist· Biochemistry, Genetics and Molecular Biology
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Woody‐tissue respiration
M. P. Lavigne
2002· article· en· New Phytologist· Medicine
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
A diversity of scales
Janice A. Lake, Julie E. Gray
2007· article· en· New Phytologist· Environmental Science
machine prediction:candidate · noneconsensus · none
1
citations
affunlabeled
Tropical forests and global change: biogeochemical responses and opportunities for cross‐site comparisons, an organized <scp>INSPIRE</scp> session at the 108<sup>th</sup> Annual Meeting, Ecological Society of America, Portland, Oregon, <scp>USA</scp>, August 2023
Daniela Cusack, Sasha C. Reed, Kelly M. Andersen, Damla Cinoğlu, Matthew E. Craig, Lee H. Dietterich +7 more
2024· article· en· New Phytologist· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
The rules of engagement
Brody J. DeYoung, Roger W. Innes
2007· article· en· New Phytologist· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations
aboutno affunlabeled
Small RNAs hit the big time
Iain Searle, Rebecca A. Mosher, Charles W. Melnyk, David C. Baulcombe
2007· article· en· New Phytologist· Agricultural and Biological Sciences
machine prediction:candidate · noneconsensus · none
1
citations

How this was built: Screen · Findings · About