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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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Synthetic Aperture Radar (SAR) Applications and Techniques
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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.

826 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.
826 works in the cohort · of 4,299,418page 11 of 17

Labels cover 1 of 826 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 826 of 826 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.

affno abstractunlabeled
A Benchmark InSAR Simulator for Phase Filtering and Coherence Estimation
Xinyao Sun, Aaron Zimmer, Navaneeth Kamballur Kottayil, Subhayan Mukherjee, Parwant Ghuman, Irene Cheng
2023· book-chapter· en· Advances in Science, Technology & Innovation/Advances in science, technology & innovation· Engineering
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
Evaluation of multiple SAR speckling filter techniques performance in irrigated rice areas
André Dalla Bernardina Garcia, Jimuel Celeste, Irene Cheng, Victor Hugo Rohden Prudente, Ieda Del’Arco Sanches
2024· article· en· ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences· Engineering
machine prediction:candidate · noneconsensus · none
2
citations
affunlabeled
AIRBORNE X-HH INCIDENCE ANGLE IMPACT ON CANOPY HEIGHT RETREIVAL: IMPLICATIONS FOR SPACEBORNE X-HH TANDEM-X GLOBAL CANOPY HEIGHT MODEL
M. Lorraine Tighe, Douglas J. King, Heiko Balzter, A. Bannari, Heather McNairn
2012· article· en· ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences· Engineering
machine prediction:candidate · noneconsensus · none
2
citations
affno abstractunlabeled
A tool for bistatic SAR geometry determinations
R.K. Hawkins, J.R. Gibson, R. Saper, M. Hilaire
2003· article· en· Advances in Space Research· Engineering
machine prediction:candidate · noneconsensus · none
2
citations
aboutno affunlabeled
EVALUATION OF INSAR DEM FROM HIGH-RESOLUTION SPACEBORNE SAR DATA
Kenji Watanabe, Umut Güneş Sefercik, Alexander Schunert, Uwe Sörgel
2012· article· en· ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences· Engineering
machine prediction:candidate · noneconsensus · none
2
citations

How this was built: Screen · Findings · About