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Record W2415321074 · doi:10.1097/aog.0000000000001474

Prescription of Hormonal Contraception by Pharmacists in Oregon

2016· article· en· W2415321074 on OpenAlexaff
María I. Rodríguez, Lorinda Anderson, Alison Edelman

Bibliographic record

VenueObstetrics and Gynecology · 2016
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsWomen's Health Research Institute
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsHormonal contraceptionLegislationMedical prescriptionPharmacistPillUnintended pregnancyFamily planningMedicineFamily medicineAuthorizationScope (computer science)Emergency contraceptionPrior authorizationDeveloped countryPharmacyGynecologyNursingBusinessPopulationPolitical scienceEnvironmental healthComputer securityComputer scienceLawResearch methodology

Abstract

fetched live from OpenAlex

Prescription of hormonal contraception by pharmacists, without a doctor's visit or authorization, has been proposed as a strategy to improve access to contraception and reduce unintended pregnancy. Oregon is the first state to implement legislation expanding the scope of pharmacists to directly prescribe and dispense short-acting hormonal contraception (pill and patch). Several other states are considering similar legislation. Implementation of the policy is being researched to identify both barriers and facilitators to the successful dissemination of the practice and to determine the safety, efficacy, and acceptability of pharmacist-prescribed 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.182
Threshold uncertainty score0.363

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.284
Teacher spread0.268 · 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 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

Citations32
Published2016
Admission routes1
Has abstractyes

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