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Record W3192952693 · doi:10.1542/neo.22-8-e521

Marijuana Use during Pregnancy and Lactation and Long-term Outcomes

2021· review· en· W3192952693 on OpenAlexaff
Nadia Narendran, Karman Yusuf

Bibliographic record

VenueNeoReviews · 2021
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineBreastfeedingPregnancyEpidemiologyPopulationPublic healthConfoundingEnvironmental healthPsychiatryPediatrics

Abstract

fetched live from OpenAlex

Recent surveys have shown increased use of marijuana during the perinatal period, possibly linked to increased legalization in many countries. Available information on the association between marijuana exposure and the effects on growth and development, as well as brain structure and function of the fetus, is growing but has not been uniform. Interpretation of these data is often challenging because of the influence of confounding factors and the sociodemographic variabilities in the study subjects. In this review, we present a synthesis of current information on the epidemiology and effects of marijuana use during pregnancy and evaluate the evidence for the immediate and long-term effects on affected neonates. We also describe the current knowledge and implications of breastfeeding and marijuana use and summarize selected current references about this practice. Finally, we provide the rationale for additional biological and population-based investigations to determine the various fetal outcomes of in-utero marijuana exposure that may assist in the establishment of prevention measures and applicable public health policies in the future.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.111
GPT teacher head0.409
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2021
Admission routes1
Has abstractyes

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