MétaCan
Menu
Back to cohort
Record W1892712685 · doi:10.1093/biosci/biv068

Assessing Ecological and Evolutionary Consequences of Growth-Accelerated Genetically Engineered Fishes

2015· article· en· W1892712685 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

VenueBioScience · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsFisheries and Oceans Canada
FundersVetenskapsrådet
KeywordsTransgenesisAdaptation (eye)BiologyFish <Actinopterygii>EcologyGenetically modified organismGrowth hormoneBiotechnologyFisheryGene

Abstract

fetched live from OpenAlex

Genetically engineered fish containing growth hormone (GH) transgenes have been synthesized for more than 25 years, now with modifications made in multiple aquacultured species. Despite significant improvements in production characteristics being realized, these fish have not yet entered commercial production. The very strong enhancement of growth rates that can arise from GH transgenesis in fish has generated public and scientific concern regarding ecological and food safety. Little ecological risk is anticipated from engineered strains kept in fully contained facilities, so the concern is largely directed toward the reliability of containment measures and determining whether robust ecological data, pertinent to nature, can be generated within research facilities to minimize uncertainty and allow reliable risk-assessment predictions. This article summarizes the growth, life history, and behavioral changes observed in GH-transgenic fish and discusses the environmental and evolutionary factors affecting the adaptation, plasticity, and fitness of transgenic fish and their potential consequences on natural ecosystems.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.216

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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.052
GPT teacher head0.284
Teacher spread0.233 · 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