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Record W3210653229 · doi:10.5281/zenodo.4279776

North Atlantic basin-scale multi-criteria assessment database to inform management recommendations to protect Vulnerable Marine Ecosystems

2020· dataset· en· W3210653229 on OpenAlexaff
Telmo Morato, Christopher K. Pham, Laurence Fauconnet, Gerald H. Taranto, Giovanni Chimienti, Erik E. Cordes, Carlos Dominguez‐Carrió, P. Durán-Muñoz, Hrönn Egilsdóttir, José Manuel González‐Irusta, Anthony Grehan, Dierk Hebbeln, Lea‐Anne Henry, Georgios Kazanidis, Ellen Kenchington, Lénàïck Menot, Tina N. Molodtsova, Covadonga Orejas, Berta Ramiro‐Sánchez, Manuela Ramos, Luís Rodrigues, Steve W. Ross, José L. Rueda, M.M. Sacau-Cuadrado, David Stirling, Marina Carreiro‐Silva

Bibliographic record

VenueEdinburgh Research Explorer (University of Edinburgh) · 2020
Typedataset
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
FundersHorizon 2020 Framework Programme
KeywordsEnvironmental resource managementScale (ratio)EcosystemMarine ecosystemMarine protected areaStructural basinEnvironmental scienceGeographyEcologyGeologyCartographyBiology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.096
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.011

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 head0.084
GPT teacher head0.335
Teacher spread0.251 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes1
Has abstractyes

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