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Record W2907460909 · doi:10.1093/pch/pxy169

A paediatric perspective on hormonal contraception and breast cancer risk: New literature about a recurring question

2019· article· en· W2907460909 on OpenAlexaff
Ellie Vyver, Loris Y. Hwang

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsHormonal contraceptionBreast cancerMedicineFamily medicineGynecologyUnintended pregnancyFamily planningAlternative medicineDeveloped countryPerspective (graphical)PregnancyCancerPopulationEnvironmental healthResearch methodologyInternal medicine

Abstract

fetched live from OpenAlex

The New England Journal of Medicine recently featured an original research article, ‘Contemporary Hormonal Contraception and the Risk of Breast Cancer’. (Source: Mørch LS, Skovlund CW, Hannaford PC, Iversen L, Fielding S, Lidegaard Ø. Contemporary hormonal contraception and the risk of breast cancer. N Engl J Med 2017;377(23):2228–39). This study of 1.8 million women ages 15 to 49 years in Denmark found that women who were currently or recently using any type of hormonal contraception had an increased risk of breast cancer and this risk increased with longer duration of use. To date, the implications of this study have focused on older female populations. In this commentary, the authors summarize the key findings of the study and discuss its unique implications for adolescents. The authors emphasize that health care providers need not change their practice as a result of this ‘old but new again’ controversy and should continue to support the prevention of unintended pregnancy by promoting access to ALL forms of contraception.

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)0.009
metaresearch head score (Gemma)0.034
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.008
Scholarly communication0.0030.007
Open science0.0020.002
Research integrity0.0070.015
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 head0.006
GPT teacher head0.291
Teacher spread0.284 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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