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Ten years later: An update on the status of collections of endemic Gulf of Mexico fishes put at risk by the 2010 Oil Spill

2023· preprint· en· W4387262141 on OpenAlexaff
Prosanta Chakrabarty, A. Sheehy, Xavier Clute, Shannon Cruz, Brandon Ballengée

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicOil Spill Detection and Mitigation
Canadian institutionsCanadian Museum of Nature
FundersLouisiana State University
KeywordsOil spillGeographyDeepwater horizonFisheryFish <Actinopterygii>EndemismDistribution (mathematics)Period (music)EcologyEnvironmental protectionBiology

Abstract

fetched live from OpenAlex

The 2010 Gulf of Mexico Deepwater Horizon was the largest spill in human history that occurred during a 12- week period over ten years ago; however, after more than a decade of post-spill research little definitive remains known about the long-term impacts on the development and distribution of fishes in and around the region of the disaster. Here we examine endemic Gulf of Mexico fish species that may have been most affected by noting their past distributions in the region of the spill and examining data of known collecting events over the last twenty years (ten years prior to the spill, ten years post spill). In addition some observational data that did not result in specimen collections are also examined here. Five years post spill, it was reported that 48 of the Gulf’s endemic fish species had not been collected, with expanded methods we now report that 29 (of the 78 endemic species) have not been reported in collections since 2010 (five of these are only known from observations post-spill). Although there is some cause to celebrate the good news that some previously ‘missing’ species have been found, the lack of information for many species remains a cause for concern.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.233
Teacher spread0.216 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2023
Admission routes1
Has abstractyes

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