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Record W4387102626 · doi:10.5194/sp-1-osr7-2-2023

Evaluation of operational ocean forecasting systems from the perspective of the users and the experts

2023· article· en· W4387102626 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueState of the Planet · 2023
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Computational Techniques and Applications
Canadian institutionsDalhousie UniversityEnvironment and Climate Change CanadaFisheries and Oceans Canada
Fundersnot available
KeywordsPerspective (graphical)Technology forecastingComputer scienceData scienceManagement scienceOperations researchMeteorologyEnvironmental scienceSystems engineeringEngineeringArtificial intelligenceGeography

Abstract

fetched live from OpenAlex

The Intergovernmental Oceanographic Commission (IOC) has an Ocean Decade Implementation Plan (UNESCO-IOC, 2021) that states seven outcomes required for the ocean we want, with the fourth outcome being “A predicted ocean where society understands and can respond to changing ocean conditions.” To facilitate the achievement of this goal, the IOC has endorsed Mercator Ocean International to implement the Decade Collaborative Center (DCC) for OceanPrediction (https://www.mercator-ocean.eu/oceanprediction/, last access: 21 August 2023), which is a cross-cutting structure that will work to develop global-scale collaboration between Decade Actions related to ocean prediction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.116

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.051
GPT teacher head0.296
Teacher spread0.245 · 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