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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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Marine animal studies overview
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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.

4,737 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
4,737 works in the cohort · of 4,299,418page 87 of 95

Labels cover 4 of 4,737 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 4,737 of 4,737 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
A__1__20170510_045056.wav
Branko Hilje, Shauna Stack, Arturo Sánchez‐Azofeifa
2019· dataset· zh· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Polar bears in action!
Sarah L. Alderman
2018· article· en· Journal of Experimental Biology· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · none
0
citations
affunlabeled
A__1__20170509_164456.wav
Branko Hilje, Shauna Stack, Arturo Sánchez‐Azofeifa
2019· dataset· hi· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)85771-7
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(98)83741-1
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
NEFSC Aerial Survey - Summer 1998
2025· dataset· en· OBIS-SEAMAP· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)81184-2
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(96)83194-2
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
Atatina albida Bartz & Decaens 2024, n. sp.
2024· article· en· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A__1__20170509_173956.wav
Branko Hilje, Shauna Stack, Arturo Sánchez‐Azofeifa
2019· dataset· hi· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)80523-6
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(93)91517-g
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
A__1__20170510_083056.wav
Branko Hilje, Shauna Stack, Arturo Sánchez‐Azofeifa
2019· dataset· hi· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Beatricea sanpabloensis
2020· article· en· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Aboriginal whale watching
Heather Zeppel
2008· book-chapter· en· ResearchOnline at James Cook University (James Cook University)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
The effect of COVID-19 on underwater sound
David R. Barclay
2021· article· en· The Journal of the Acoustical Society of America· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Coast stock
2013· article· en· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
aboutno affunlabeled
Hotspots of Hector’s Dolphins On the South Coast
Judy Rodda, Antoni Moore
2013· article· en· Otago University Research Archive (University of Otago)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
Blubber news: whale fat is active!
Oana Birceanu
2017· article· en· Journal of Experimental Biology· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(95)91867-4
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
A__1__20170511_061956.wav
Branko Hilje, Shauna Stack, Arturo Sánchez‐Azofeifa
2019· dataset· hi· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/0967-0653(96)86029-7
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)87305-x
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
A__1__20170510_185756.wav
Branko Hilje, Shauna Stack, Arturo Sánchez‐Azofeifa
2019· dataset· hi· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
aboutno affunlabeled
Tetranychus turkestani
2011· article· en· Zenodo (CERN European Organization for Nuclear Research)· Environmental Science
machine prediction:candidate · noneconsensus · none
0
citations
affunlabeled
A__1__20170511_070356.wav
Branko Hilje, Shauna Stack, Arturo Sánchez‐Azofeifa
2019· dataset· hi· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
venueno affno abstractunlabeled
10.1016/s0967-0653(97)82285-5
2000· article· en· Time to knit· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations
affunlabeled
A__1__20170510_161256.wav
Branko Hilje, Shauna Stack, Arturo Sánchez‐Azofeifa
2019· dataset· hi· Harvard Dataverse· Environmental Science
machine prediction:candidate · insufficient_payloadconsensus · insufficient_payload
0
citations

How this was built: Screen · Findings · About