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Record W4253397544 · doi:10.1021/bk-2010-1048.ch022

Assessment of the Aquatic Release and Relevance of Selected Endogenous Chemicals: Androgens, Thyroids and Their<i>in Vivo</i>Metabolites

2010· book-chapter· en· W4253397544 on OpenAlexaff
Usman Khan, Jim A. Nicell

Bibliographic record

VenueACS symposium series · 2010
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsMcGill University
Fundersnot available
KeywordsEndogenyRelevance (law)In vivoChemistryPharmacologyEnvironmental chemistryBiologyBiochemistryBiotechnologyPolitical science

Abstract

fetched live from OpenAlex

Endogenous chemicals released through anthropogenic excretions enter the environment on a continuous basis. Therefore, it is important to establish their rate of introduction into the environment. An approach was developed to establish such environmental loads for any given endogenous chemical that is likely to be released in anthropogenic excretions. The approach developed was used to quantify influent, effluent and surface water loads of 25 endogenous chemicals including androgens, thyroids and their in vivo metabolites, using the United States as an illustrative case. The predicted surface water concentrations matched up well with the limited monitoring data presently available. The environmental relevance of the surface water presence could only be assessed for 5 of the 25 endogenous chemicals due to limited availability of eco-toxicological data. Data available thus far suggest that testosterone, dihydrotestosterone, thyroxine, triiodothyronine are unlikely to pose a risk to the receiving aquatic ecosystem when considered individually. However, androstenedione is predicted to pose a potential risk to the receiving environment in situations where the surface water dilution of the effluents is expected to be low.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.913

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 head0.012
GPT teacher head0.225
Teacher spread0.214 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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