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Life‐course epidemiology: concepts and theoretical models and its relevance to chronic oral conditions

2007· article· en· W1967531478 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

VenueCommunity Dentistry And Oral Epidemiology · 2007
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsMcGill UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsLife course approachMedicinePsychosocialEpidemiologyDiseaseDisadvantageEtiologyGerontologyAffect (linguistics)Chronic diseaseIntensive care medicineDevelopmental psychologyPsychiatryPathologyPsychology

Abstract

fetched live from OpenAlex

Etiological models that predominantly emphasize current adult life styles, such as smoking, diet and lack of exercise have recently been seriously challenged by a growing body of evidence that disturbed early growth and development, childhood infection, poor nutrition, and social and psychosocial disadvantage across the life-course affect chronic disease risk, including chronic oral disease. This relatively new area of research is called life-course epidemiology. The life-course framework for investigating the aetiology and natural history of chronic disease proposes that advantages and disadvantages are accumulated throughout life generating differentials in health along the life-course, but most importantly later in life. Furthermore, its dynamic framework brings together the effects of intrinsic factors (individual resources) with extrinsic factors (environmental factors). The aim of this paper is to give an overview of this new epidemiological approach and to discuss how the life-course framework has been applied to chronic oral conditions.

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)0.008
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.131
GPT teacher head0.452
Teacher spread0.321 · 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