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Record W6940909066 · doi:10.11575/prism/28598

Urban-Derived Contaminants Cause Reproductive Disruption in an Aquatic Sentinel Species, Longnose Dace

2014· other· en· W6940909066 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2014
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsSentinel speciesContaminationAquatic animalVitellogeninInvertebrateEffluentEndocrine disruptorReproductionFish <Actinopterygii>

Abstract

fetched live from OpenAlex

We investigated potential adverse impacts of urban-derived environmental contaminants, such as pharmaceuticals, steroids, surfactants and plasticizers, on Longnose Dace (Rhinichthys cataractae) along two rivers, the Bow and Elbow Rivers, in the City of Calgary. Fish were sampled to evaluate physiological and morphological endpoints associated with reproduction and development, including adult sex ratios, changes in body and organ weight, and gonad malformation. Significant male bias was observed downstream of three wastewater treatment plants (WWTPs) on the Bow River, and significant female bias was observed on the Elbow River, suggesting the presence of environmental contaminants with hormone-like activity, dependent on location. To investigate the mechanisms of adverse fish health effects we quantified the expression of liver vitellogenin, estrogen receptor alpha, cytochrome P450, and insulin-like growth factor-1. Decreased IGF1 and ERα expression levels were observed downstream of WWTP effluent in the Bow River, while increased vitellogenin and ERα expression levels were noted in the Elbow River within Calgary. Results support the hypothesis that waterborne environmental contaminants may be responsible for the adverse health effects, such as biased sex ratios, of Longnose Dace within the City of Calgary.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.684
Threshold uncertainty score0.993

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)0.0070.000

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 head0.015
GPT teacher head0.201
Teacher spread0.186 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2014
Admission routes1
Has abstractyes

Explore more

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