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Record W2321529314 · doi:10.5171/2014.369374

Marijuana Exposure During Lactation: Is It Safe?

2014· article· en· W2321529314 on OpenAlexaff
Alice Ordean

Bibliographic record

VenuePediatrics Research International Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsSt Joseph's Health CentreUniversity of Toronto
Fundersnot available
KeywordsLactationMedicinePregnancyBiologyGenetics

Abstract

fetched live from OpenAlex

The aim of this paper is to provide a systematic review of the evidence regarding the safety of cannabis exposure during lactation and recommendations for clinical practice.PubMed and OVID Medline search was performed using pregnancy, breastfeeding, cannabis, and marijuana.Articles were limited to human studies and English language.Animal studies, case reports, reviews and letters were excluded.Four studies were included in this review.Based on current evidence, there is one study reporting a potential effect of marijuana on motor development at one year of age.However, this finding was not repeated in other studies.Most evidence of harm is associated with prenatal exposure.Women need to be advised that the risk of exposure to marijuana during lactation remains uncertain; therefore, risks and benefits of marijuana use need to be considered before deciding to breastfeed.

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)0.011
metaresearch head score (Gemma)0.062
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 score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.062
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.416
Teacher spread0.362 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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