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Record W6939736279 · doi:10.6084/m9.figshare.29327468

A Review of American Lobster (<i>Homarus americanus</i>) Research Since 2000

2025· article· en· W6939736279 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsAmerican lobsterContext (archaeology)Quarter (Canadian coin)FishingHomarusEcosystemClimate change

Abstract

fetched live from OpenAlex

The last quarter century has produced a remarkable amount of scientific research on the data-rich and immensely important American lobster (Homarus americanus). In fact, more than 1000 peer-reviewed papers have been published on the species since 2000, advancing all aspects of lobster science, research, and management. Many of these efforts have been motivated by large-scale alterations in ecosystems in the Northwest Atlantic due to climate change, including changes in temperature, water chemistry, ecosystem productivity, and oceanography. These changes have driven researchers to focus on the many direct and indirect impacts that climate change has had on the most valuable single-species fishery in North America. The goal of this review is to provide a summary of the major findings in lobster science over the last quarter century, with an emphasis on how anthropogenic impacts and environmental modifications might impact lobsters and the lobster fishery in the future as well as to serve as a touchstone for the next 25 years within the context of a dynamic and changing ecosystem. This review also includes a summary of important topics and ideas for further research, especially those with knowledge gaps, in the hope that it can help guide future approaches to American lobster research and further improvements to fisheries management.

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)0.003
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
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.044
GPT teacher head0.341
Teacher spread0.296 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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