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Record W2751272121

Knowledge of the effects of gestational alcohol consumption and FASD in an Ontarian sample

2017· dissertation· en· W2751272121 on OpenAlexaboutno aff
Alexandra M. Zidenberg

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2017
Typedissertation
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsnot available
Fundersnot available
KeywordsAlcohol consumptionSample (material)Consumption (sociology)Environmental healthPsychologyAlcoholMedicineSociologySocial scienceChemistryBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

The current document is a two-paper manuscript-based thesis investigating what women in
\nOntario know about drinking during the gestational period. Though there have been many studies
\ninvestigating what women in various countries and locations know about drinking during
\npregnancy, there is a lack of recent data focusing on Ontario, Canada. Both papers use a surveybased
\napproach to answer the research questions posed in each respective manuscript. The first
\npaper explored what women currently know about drinking during pregnancy and what
\nindividual characteristics may influence endorsement of drinking behaviours. The majority of
\nparticipants did not endorse drinking behaviours, however, a small but substantial portion of the
\npopulation still endorses drinking. The second manuscript addressed where individuals receive
\ntheir information about drinking during the gestational period. Results indicated that women in
\nOntario saw information in print and news media, but would most prefer to get their information
\nfrom health care professionals. Implications in terms of education and prevention are discussed.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.910

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 studies0.0000.000
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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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