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Estimation of Fetal Exposure to Drugs of Abuse, Environmental Tobacco Smoke, and Ethanol

2002· review· en· W2313872411 on OpenAlex
Gideon Koren, Daphne Chan, Julia Klein, Tatiana Karaskov

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTherapeutic Drug Monitoring · 2002
Typereview
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoSickKids Foundation
Fundersnot available
KeywordsMeconiumRecreational DrugPregnancyMedicineToxicantFetusPhysiologyHair analysisEnvironmental healthPharmacologyObstetricsDrugToxicologyToxicityInternal medicineBiologyPathology

Abstract

fetched live from OpenAlex

Many women worldwide use recreational drugs and alcohol. Details on the amounts and schedule of such exposures in pregnancy are often unreliable because of recall issues and shame and fears of legal action. Even when the report on maternal dose is correct, it does not necessarily reflect the amount reaching the fetus. Drugs of abuse accumulate in meconium and are incorporated into fetal hair on its growth. Recent work has documented the sensitivity and specificity of these assays for cocaine and other recreational drugs. Dose-response relationships between cocaine as measured in neonatal hair and head circumference or neurologic sequelae have been recently established. For ethanol, which cannot be measured in hair or meconium, accumulation of its fatty acid ethyl esters in meconium is emerging as a promising test for heavy maternal drinking in the second part of pregnancy. The identification of biologic markers of intrauterine exposure to xenobiotics will allow better understanding of etiology and dose-response relationships.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.039
GPT teacher head0.311
Teacher spread0.273 · 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