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Record W3021451169 · doi:10.1016/j.jmwh.2003.08.004

Our students: a breath of fresh air

2003· article· en· W3021451169 on OpenAlexaboutno aff
Laura Zeidenstein

Bibliographic record

VenueJournal of Midwifery & Women s Health · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsTroutSalvelinusEnvironmental scienceFisheryFish <Actinopterygii>Fish consumptionEcologyBiology

Abstract

fetched live from OpenAlex

We evaluate the temporal trends of total mercury (THg) and polychlorinated biphenyls (PCBs) in walleye (Sander vitreus) and lake trout (Salvelinus namaycush) based on approximately 40 years of contaminant data from different locations in Lake Ontario. Bayesian inference techniques are employed to parameterize four hierarchical models. Our analysis provides evidence of distinctly declining trajectories for the two contaminants in lake trout. Likewise, walleye demonstrate a decreasing PCB trend, whereas no distinct temporal shifts were found in their THg rates of change. We illustrate the capacity of our statistical framework to aid in formulating fish consumption advisories by generating customizable probability of exceedance of THg and PCB threshold human exposure levels, based on their tolerable daily intake values. Walleye consumption results in 30% lakewide exceedance frequencies of the THg threshold for the sensitive demographic group of children less than 15 years old with an average body weight of 50 kg. Lake trout PCB threshold is frequently exceeded (> 80%) in all of the study sites, whereas exposure to THg through lake trout consumption appears to be within the acceptable levels for human health. The overall trends indicate that the reduced contaminant emissions have brought about positive changes in the fish contamination levels in Lake Ontario.

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)0.003
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 score0.088
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0010.000

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 head0.029
GPT teacher head0.343
Teacher spread0.314 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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