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Record W2115830987 · doi:10.1093/ije/dyu135

Cohort Profile: The Nicotine Dependence in Teens (NDIT) Study

2014· article· en· W2115830987 on OpenAlexafffundabout
Jennifer O’Loughlin, Erika N. Dugas, Jennifer Brunet, Joseph R. DiFranza, James C. Engert, André Gervais, Katherine Gray-Donald, Igor Karp, Nancy Low, Catherine Sabiston, Marie-Pierre Sylvestre, Rachel F. Tyndale, Nathalie Auger, Belanger Mathieu, Barnett Tracie, Michael Chaiton, Meghan J. Chenoweth, Evelyn Constantin, Gisèle Contreras, Lisa Kakinami, Aurélie Labbe, Katerina Maximova, Elizabeth McMillan, Erin K. O’Loughlin, Roman Pabayo, Marie‐Hélène Roy‐Gagnon, Michèle Tremblay, Robert J. Wellman, Andraea Van Hulst, Gilles Paradis

Bibliographic record

VenueInternational Journal of Epidemiology · 2014
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsCentre for Addiction and Mental HealthUniversity of TorontoMcGill University Health CentreUniversité de MontréalMcGill UniversityCentre Hospitalier de l’Université de MontréalUniversity of OttawaInstitut National de Santé Publique du Québec
FundersCanadian Institutes of Health Research
KeywordsMedicineGraduation (instrument)CohortFamily medicineMental healthNicotineObesityCohort studyGerontologyPsychologyPsychiatry

Abstract

fetched live from OpenAlex

The Nicotine Dependence in Teens (NDIT) study is a prospective cohort investigation of 1294 students recruited in 1999-2000 from all grade 7 classes in a convenience sample of 10 high schools in Montreal, Canada. Its primary objectives were to study the natural course and determinants of cigarette smoking and nicotine dependence in novice smokers. The main source of data was self-report questionnaires administered in class at school every 3 months from grade 7 to grade 11 (1999-2005), for a total of 20 survey cycles during high school education. Questionnaires were also completed after graduation from high school in 2007-08 and 2011-12 (survey cycles 21 and 22, respectively) when participants were aged 20 and 24 years on average, respectively. In addition to its primary objectives, NDIT has embedded studies on obesity, blood pressure, physical activity, team sports, sedentary behaviour, diet, genetics, alcohol use, use of illicit drugs, second-hand smoke, gambling, sleep and mental health. Results to date are described in 58 publications, 20 manuscripts in preparation, 13 MSc and PhD theses and 111 conference presentations. Access to NDIT data is open to university-appointed or affiliated investigators and to masters, doctoral and postdoctoral students, through their primary supervisor (www.nditstudy.ca).

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)0.005
metaresearch head score (Gemma)0.005
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 score0.007
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
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)0.0000.000

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 head0.054
GPT teacher head0.401
Teacher spread0.347 · 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

Citations93
Published2014
Admission routes3
Has abstractyes

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