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Record W1967954068 · doi:10.1289/ehp.02110881

Y-chromosomal DNA markers for discrimination of chemical substance and effluent effects on sexual differentiation in salmon.

2002· article· en· W1967954068 on OpenAlexaff
Jack L. Smith, Michael G. Ikonomou, Robert H. Devlin

Bibliographic record

VenueEnvironmental Health Perspectives · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReproductive biology and impacts on aquatic species
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsSexual differentiationBiologySecondary sex characteristicDevelopment of the gonadsEffluentSewageFish <Actinopterygii>PhysiologyGonadAndrologyGeneticsZoologyEndocrinologyGeneHormoneMedicineFishery

Abstract

fetched live from OpenAlex

Chinook salmon alevins were exposed during their labile period for sex differentiation to different concentrations of bleached kraft mill effluent (BKME), primary sewage effluent, secondary sewage effluent (SE), 17ss-estradiol, testosterone, and nonylphenol. After exposure for 29 days post hatching (DPH), fish were allowed to grow until 103 and 179 DPH, at which time their genetic sex was determined using Y-chromosomal DNA markers and their gonadal sex was determined by histology. Independent of treatment, all fish identified as genetic females (XX) in these experiments possessed normal female gonads. Only the highest dose of some treatments affected the development of gonads in genetic XY males. At 103 DPH, some genetic males treated with 1 micro g estradiol/L, BKME 100%,and SE 30% developed as physiological females, presenting ovaries identical to genetic females in the control group. The physiological female condition in XY fish was also observed in these treatments groups at 179 DPH, which suggests that the effect is permanent, whereas in other groups the effect changed between sampling periods. Identification of the genetic sex of individual animals using sex-linked DNA markers provides a useful tool for investigating environmental factors influencing sex determination and differentiation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.417

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)0.0000.000

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 head0.255
Teacher spread0.243 · 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 designBench or experimental
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

Citations43
Published2002
Admission routes1
Has abstractyes

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