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Supplementary material to "A compilation of global bio-optical in situ data for ocean-colour satellite applications – version three"

2022· preprint· en· W4290691972 on OpenAlexfundno aff
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Thomas J. Jackson, A.D. Chuprin, Malcolm Taberner, Ruth L. Airs, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean‐François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Robert J. W. Brewin, Elisabetta Canuti, Francisco P. Chavez, A. Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Afonso Ferreira, Scott Freeman, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Ralf Goericke, Richard A. Gould, Nathalie Guillocheau, Stanford B. Hooker, Chuamin Hu, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael M. Kudela, Jesús Ledesma, Steven E. Lohrenz, Hubert Loisel, Antonio Mannino, Víctor Martínez-Vicente, Patricia A. Matrai, David McKee, B. Greg Mitchell, Tiffany Moisan, Enrique Montes, Frank Müller‐Karger, Aimee Neeley, Michael Novák, Leonie O’Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Répécaud, Rüdiger Röttgers, Thomas Schroeder, Tim Smyth, Denise Smythe‐Wright, Heidi M. Sosik, Crystal Thomas, Robert E. Thomas, Gavin H. Tilstone, Andreia Tracana, Michael Twardowski, Vincenzo Vellucci, Kenneth J. Voss, Jeremy Werdell, Marcel Robert Wernand, Bożena Wojtasiewicz, Simon Wright, Giuseppe Zibordi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicEnvironmental Monitoring and Data Management
Canadian institutionsnot available
FundersNational Marine Fisheries ServiceOffice of Polar ProgramsInstitut national des sciences de l'UniversNatural Environment Research CouncilUniversity of California, San DiegoCalifornia Department of Fish and WildlifeGoddard Space Flight CenterCentre National de la Recherche ScientifiqueBundesministerium für Bildung und ForschungSorbonne UniversitéNational Oceanic and Atmospheric AdministrationDeutsche ForschungsgemeinschaftFisheries and Oceans CanadaEuropean CommissionNational Science FoundationEuropean Space AgencyNational Aeronautics and Space AdministrationCentre National d’Etudes SpatialesCommonwealth Scientific and Industrial Research OrganisationEuropean Organization for the Exploitation of Meteorological Satellites
KeywordsIn situSatelliteRemote sensingEnvironmental scienceComputer scienceGeologyMeteorologyGeographyPhysicsAstronomy

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.628
Threshold uncertainty score0.531

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.6280.347

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.276
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractno

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