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Record W4307919925

Association of Smoking Habits of Mother during Pregnancy with Pregnancy Outcome

2013· article· en· W4307919925 on OpenAlexaffabout
Cyrus Azimi, Mahshid Lotfi

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsPregnancyObstetricsOutcome (game theory)MedicineAssociation (psychology)PsychologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Background: The objectives of this work were to study the association of maternal smoking habits with stillbirths, abortions, neonatal deaths, birth weights, placental weights and the outcomes on the 28th day of life.Methods: A questionnaire was developed and completed with the hospitals' recorded data collected over a period of 5 years from 47,000 babies born in several hospitals in Ontario, Canada. The mothers were classified into four categories: non-smokers, light smokers (less than 10 cigarettes per day), moderate smokers (between 10 and 19 cigarettes per day) and heavy smokers (20 or more cigarettes per day). The population surveyed was of mixed ethnicity from both rural and urban areas. Statistical analysis was performed using the SPSS statistical package.Results: Even the light smoking habit has an effect on the birth weight and the placental weight but for other characteristics, stillbirth, abortion, and the outcomes on the 28th day of life, no significant difference observed between light smokers and non-smokers.Conclusion: While quit smoking must be the ultimate goal for any smoker, the present study concludes that moderate and heavy smokers, if they will not be able to quit, they should reduce their number of cigarettes per day to at least the level of light smokers to achieve the same results for non-smokers. All characteristics show significant difference between non-smokers and moderate and heavy smokers.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.000

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 head0.281
GPT teacher head0.607
Teacher spread0.326 · 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.

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
Published2013
Admission routes2
Has abstractyes

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