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Record W4231245699 · doi:10.1080/15287390309353771

CYP1A INDUCTION AND BLUE SAC DISEASE IN EARLY DEVELOPMENTAL STAGES OF RAINBOW TROUT<i>(ONCORHYNCHUS MYKISS)</i>EXPOSED TO RETENE

2003· article· en· W4231245699 on OpenAlexaff
Lyndon Brinkworth, Peter V. Hodson, Samir Tabash, Patricia Lee

Bibliographic record

VenueJournal of Toxicology and Environmental Health · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsQueen's UniversityFisheries and Oceans Canada
Fundersnot available
KeywordsRainbow troutToxicityYolk sacBiologyOntogenyExcretory systemHuman fertilizationAndrologyImmunohistochemistryLarvaPhysiologyEmbryoFish <Actinopterygii>AnatomyInternal medicineEndocrinologyMedicineFisheryImmunologyEcology

Abstract

fetched live from OpenAlex

Abstract Early life stages of rainbow trout were exposed to different regimes of water-borne retene (7-isopropyl-1-methylphenanthrene) to determine if there is an ontogenic stage particularly sensitive to retene toxicity, and if cytochrome P-4501A (CYP1A) induction is a forerunner to blue sac disease (BSD), the syndrome of toxicity. CYP1A protein concentrations, measured by immunohistochemistry, were first detected during organogenesis, when organ and enzyme systems are first being developed, and steadily increased until swim-up. The prevalence of signs of BSD rose 1 wk following a marked increase in CYP1A activity after hatch, suggesting that CYP1A induction is related to BSD. The larval stage was the most sensitive to retene toxicity, based on CYP1A induction and a high prevalence of BSD. The most common signs of BSD were hemorrhaging, yolk-sac edema, and mortality, but hemorrhaging was the first and most frequently observed response. Tissue concentrations of retene were elevated just afte fertilization, but decreased steadily as fish developed to the swim-up stage, most likely due to the establishment of more efficient metabolic and excretory systems in later stages of development.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.012
GPT teacher head0.231
Teacher spread0.219 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations83
Published2003
Admission routes1
Has abstractyes

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