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Record W4381295391 · doi:10.1017/ext.2023.11.pr6

Decision: A review of recent and future marine extinctions — R0/PR6

2023· review· en· W4381295391 on OpenAlexaff

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of British Columbia
FundersComisión de Operación y Fomento de Actividades Académicas, Instituto Politécnico NacionalInstituto Politécnico Nacional
KeywordsExtinction (optical mineralogy)Extinction eventBiodiversityMarine biodiversityFaunaGeographyEcologyMarine speciesGlobal biodiversityEnvironmental scienceBiologyPaleontologyPopulationBiological dispersal

Abstract

fetched live from OpenAlex

Between 20 and 24 marine extinctions, ranging from algal to mammal species, have occurred over the past 500 years. These relatively low numbers question whether the sixth mass extinction that is underway on land is also occurring in the ocean. There is, however, increasing evidence of worldwide losses of marine populations that may foretell a wave of oncoming marine extinctions. A review of current methods being used to determine the loss of biodiversity from the world’s oceans reveals the need to develop and apply new assessment methodologies that incorporate standardized metrics that allow comparisons to be made among different regions and taxonomic groups, and between current extinctions and past mass extinction events. Such efforts will contribute to a better understanding of extinction risk facing marine flora and fauna, as well as the ways in which it can be mitigated.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0160.006

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 head0.077
GPT teacher head0.368
Teacher spread0.291 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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