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Record W2994178804

YOUTH AND THE OPIOID CRISIS: STRATEGIES FOR INTERVENTION AND THE BRITISH COLUMBIAN EXPERIENCE

2018· article· en· W2994178804 on OpenAlexaffvenueabout
Christina Schweitzer, Stephanie Gill, A. Laurence Kennedy, Kate Eppler

Bibliographic record

VenueUBC Faculty of Medicine medical journal · 2018
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
Keywords(+)-NaloxoneOpioid overdoseHarm reductionIntervention (counseling)MedicineOpioidHarmPublic healthAddictionCrisis interventionMedical emergencyPsychiatryPsychologyNursingSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

The opioid crisis is a growing public health concern in Canada, and especially in British Columbia, which has declared it a public health emergency. In response to the rising number of youth overdose deaths, BC has implemented a number of harm reduction and prevention strategies. Areas for continued improvement include naloxone kit training, encouraging users to not use alone and for bystanders to call 911 in the event of an overdose, and minimizing risk factors for addiction while maximizing protective factors. As the opioid crisis continues it spread east, other jurisdictions have much to learn from the BC experience.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0240.008
Scholarly communication0.0060.003
Open science0.0020.008
Research integrity0.0030.010
Insufficient payload (model declined to judge)0.0100.000

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 head0.025
GPT teacher head0.330
Teacher spread0.305 · 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 designQualitative
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

Citations1
Published2018
Admission routes3
Has abstractyes

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