MétaCan
Menu
Back to cohort
Record W2036179026 · doi:10.1097/ftd.0b013e3181957a3b

Methods for Quantification of Exposure to Cigarette Smoking and Environmental Tobacco Smoke: Focus on Developmental Toxicology

2009· review· en· W2036179026 on OpenAlex

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 · 2009
Typereview
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Center for Research Resources
KeywordsCotinineTobacco smokeNicotineEnvironmental healthBiomarkerMedicineCigarette smokeExposure assessmentSmokeless tobaccoCigarette smokingRecall biasToxicologyPathologyTobacco useInternal medicineBiologyPopulation

Abstract

fetched live from OpenAlex

Active and passive smoking have been associated with an array of adverse effects on health. The development of valid and accurate scales of measurement for exposures associated with health risks constitutes an active area of research. Tobacco smoke exposure still lacks an ideal method of measurement. A valid estimation of the risks associated with tobacco exposure depends on accurate measurement. However, some groups of people are more reluctant than others to disclose their smoking status and exposure to tobacco. This is particularly true for pregnant women and parents of young children, whose smoking is often regarded as socially unacceptable. For others, recall of tobacco exposure may also prove difficult. Because relying on self-report and the various biases it introduces may lead to inaccurate measures of nicotine exposure, more objective solutions have been suggested. Biomarkers constitute the most commonly used objective method of ascertaining nicotine exposure. Of those available, cotinine has gained supremacy as the biomarker of choice. Traditionally, cotinine has been measured in blood, saliva, and urine. Cotinine collection and analysis from these sources has posed some difficulties, which have motivated the search for a more consistent and reliable source of this biomarker. Hair analysis is a novel, noninvasive technique used to detect the presence of drugs and metabolites in the hair shaft. Because cotinine accumulates in hair during hair growth, it is a unique measure of long-term, cumulative exposure to tobacco smoke. Although hair analysis of cotinine holds great promise, a detailed evaluation of its potential as a biomarker of nicotine exposure, is needed. No studies have been published that address this issue. Because the levels of cotinine in the body are dependent on nicotine metabolism, which in turn is affected by factors such as age and pregnancy, the characterization of hair cotinine should be population specific. This review aims at defining the sensitivity, specificity, and clinical utilization of different methods used to estimate exposure to cigarette smoking and environmental tobacco smoke.

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)0.001
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 score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.120
GPT teacher head0.417
Teacher spread0.297 · 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