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Record W2287358019 · doi:10.2105/ajph.2016.303062

Increase in Naloxone Prescriptions Dispensed in US Retail Pharmacies Since 2013

2016· article· en· W2287358019 on OpenAlexaboutno aff
Christopher M. Jones, Peter Lurie, Wilson M. Compton

Bibliographic record

VenueAmerican Journal of Public Health · 2016
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
Fundersnot available
Keywords(+)-NaloxoneMedical prescriptionQuarter (Canadian coin)PharmacyMedicineHeroinOpioid epidemicFamily medicineMedical emergencyOpioidPsychiatryNursingGeographyDrugInternal medicine

Abstract

fetched live from OpenAlex

Distribution of naloxone, traditionally through community-based naloxone programs, is a component of a comprehensive strategy to address the epidemic of prescription opioid and heroin overdose deaths in the United States. Recently, there has been increased focus on naloxone prescription in the outpatient setting, particularly through retail pharmacies, yet data on this practice are sparse. We found an 1170% increase in naloxone dispensing from US retail pharmacies between the fourth quarter of 2013 and the second quarter of 2015. These findings suggest that prescribing naloxone in the outpatient setting complements traditional community-based naloxone programs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.217
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.334
Teacher spread0.289 · 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.

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

Citations72
Published2016
Admission routes1
Has abstractyes

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