MétaCan
Menu
Back to cohort
Record W4200623076 · doi:10.3389/fmars.2021.724913

A Global Ocean Oxygen Database and Atlas for Assessing and Predicting Deoxygenation and Ocean Health in the Open and Coastal Ocean

2021· article· en· W4200623076 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

VenueFrontiers in Marine Science · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsFisheries and Oceans CanadaOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNational Oceanic and Atmospheric AdministrationMinistero dell’Istruzione, dell’Università e della RicercaBelgian Federal Science Policy OfficeFundação para a Ciência e a TecnologiaFonds De La Recherche Scientifique - FNRSEuropean CommissionAgencia Nacional de Investigación y DesarrolloNorges ForskningsrådAgence Nationale de la RechercheNational Science Foundation
KeywordsDeoxygenationOceanographyPelagic zoneEnvironmental scienceAtlas (anatomy)Ocean observationsGeologyBiology

Abstract

fetched live from OpenAlex

In this paper, we outline the need for a coordinated international effort toward the building of an open-access Global Ocean Oxygen Database and ATlas (GO 2 DAT) complying with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). GO 2 DAT will combine data from the coastal and open ocean, as measured by the chemical Winkler titration method or by sensors (e.g., optodes, electrodes) from Eulerian and Lagrangian platforms (e.g., ships, moorings, profiling floats, gliders, ships of opportunities, marine mammals, cabled observatories). GO 2 DAT will further adopt a community-agreed, fully documented metadata format and a consistent quality control (QC) procedure and quality flagging (QF) system. GO 2 DAT will serve to support the development of advanced data analysis and biogeochemical models for improving our mapping, understanding and forecasting capabilities for ocean O 2 changes and deoxygenation trends. It will offer the opportunity to develop quality-controlled data synthesis products with unprecedented spatial (vertical and horizontal) and temporal (sub-seasonal to multi-decadal) resolution. These products will support model assessment, improvement and evaluation as well as the development of climate and ocean health indicators. They will further support the decision-making processes associated with the emerging blue economy, the conservation of marine resources and their associated ecosystem services and the development of management tools required by a diverse community of users (e.g., environmental agencies, aquaculture, and fishing sectors). A better knowledge base of the spatial and temporal variations of marine O 2 will improve our understanding of the ocean O 2 budget, and allow better quantification of the Earth’s carbon and heat budgets. With the ever-increasing need to protect and sustainably manage ocean services, GO 2 DAT will allow scientists to fully harness the increasing volumes of O 2 data already delivered by the expanding global ocean observing system and enable smooth incorporation of much higher quantities of data from autonomous platforms in the open ocean and coastal areas into comprehensive data products in the years to come. This paper aims at engaging the community (e.g., scientists, data managers, policy makers, service users) toward the development of GO 2 DAT within the framework of the UN Global Ocean Oxygen Decade (GOOD) program recently endorsed by IOC-UNESCO. A roadmap toward GO 2 DAT is proposed highlighting the efforts needed (e.g., in terms of human resources).

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)0.002
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 score0.060
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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