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Record W2159015627 · doi:10.1080/1755876x.2015.1049883

The current status of the real-time <i>in situ</i> Global Ocean Observing System for operational oceanography

2015· article· en· W2159015627 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

VenueJournal of Operational Oceanography · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsFisheries and Oceans Canada
FundersNational Oceanic and Atmospheric Administration
KeywordsData assimilationOcean observationsRobustness (evolution)Computer scienceEnvironmental scienceOceanographyMeteorologyData scienceClimatologySystems engineeringGeologyGeographyEngineering

Abstract

fetched live from OpenAlex

The GODAE-OceanView collection of papers primarily concerns the development of ocean data-assimilation models for operational oceanography. However, these models cannot function without a secure supply of in situ ocean data in near real-time. Several projects and programmes supply such data. The purpose of this paper is to review these data sources and describe the history, present status, future and robustness of these programmes. The conclusion is that though challenges continue with some components of the Global Ocean Observing System, overall the system continues to evolve and improve. The data are available in real-time to drive assimilation models, and expectations are increasing for more observational data. The prospects for the next 10 years seem to be good. All of the systems are evolving and there is little doubt that the Global Ocean Observing System will look different 10 years from now as new technologies emerge and capabilities improve.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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