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Record W4404992139 · doi:10.1016/j.therap.2024.11.008

Monitoring opioid analgesic misuse, abuse and dependence: What to the data from addictovigilance tell us about the situation in France?

2024· review· en· W4404992139 on OpenAlexaboutno aff
Maryse Lapeyre‐Mestre, Célian Bertin, Constança Jalles, Thomas Soeiro, Joëlle Micallef, Anne Roussin

Bibliographic record

VenueTherapies · 2024
Typereview
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsAnalgesicOpioidOpioid abusePsychiatryPsychologyMedicineAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

The opioid epidemic has emerged in the USA in the late 1990s and widespread to Canada, Australia, and the UK to a lesser extent in the more recent years. At the European level, several studies performed in different European countries have highlighted that prescription opioid use increased substantially over the last decade, and several proxies for misuse show a parallel increasing trend. The French addictovigilance experience on opioid analgesics is a good example of a specific dedicated monitoring, taking into account in a global and multisource perspective, patterns of utilization, population involved in problematic use, ways of acquisition and health complications. The added value of this data triangulation is illustrated by the recent data on tramadol and oxycodone. The addictovigilance monitoring is particularly relevant to identify early signals of potential problematic use and to assess the impact of campaigns for opioid analgesics rational use and regulatory changes.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.070
GPT teacher head0.371
Teacher spread0.301 · 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 designOther design
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

Citations5
Published2024
Admission routes1
Has abstractyes

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