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Record W3045816435 · doi:10.1038/s43017-020-0068-4

Keeping pace with marine heatwaves

2020· review· en· W3045816435 on OpenAlexaff
Neil J. Holbrook, Alex Sen Gupta, Eric C. J. Oliver, Alistair J. Hobday, Jessica A. Benthuysen, Hillary A. Scannell, Dan A. Smale, Thomas Wernberg

Bibliographic record

VenueNature Reviews Earth & Environment · 2020
Typereview
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsDalhousie University
FundersAustralian Research CouncilNational Oceanic and Atmospheric AdministrationClimate ExtremesUniversity of TasmaniaAustralian GovernmentCommonwealth Scientific and Industrial Research OrganisationUK Research and Innovation
KeywordsPredictabilityMarine ecosystemEnvironmental scienceEnvironmental resource managementStakeholderClimate changeEcosystemOceanographyEcologyPolitical scienceGeologyBiology

Abstract

fetched live from OpenAlex

Prolonged extreme oceanic warm water events, known as marine heatwaves, can have devastating impacts on marine ecosystems. This Perspective explores the predictability of marine heatwaves, taking into account the physical drivers, monitoring and prediction approaches, and stakeholder considerations.

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.

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)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.018
GPT teacher head0.253
Teacher spread0.235 · 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
GenreReview

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

Citations450
Published2020
Admission routes1
Has abstractyes

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