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Record W4229874078 · doi:10.21203/rs.3.rs-150691/v1

Use of Alcohol, Tobacco, Cannabis, and Other Substances During the First Wave of the SARS-CoV-2 Pandemic in Europe: a Survey on 36,000 European Substance Users

2021· preprint· en· W4229874078 on OpenAlexaff
Jakob Manthey, Carolin Kilian, Sinclair Carr, Miroslav Barták, Kim Bloomfield, Fleur Braddick, Antoni Gual, Maria Neufeld, Amy O’Donnell, Benjamin Petruželka, Vladimír Rogalewicz, Ingeborg Rossow, Bernd Schulte, Jürgen Rehm

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsCentre for Addiction and Mental Health
FundersNorwegian Institute of Public HealthMinistry of Health of the Russian FederationUniversitat de BarcelonaHáskóli ÍslandsUniversity of CreteKarolinska InstitutetHelsingin YliopistoTechnische Universität DresdenBudapesti Corvinus EgyetemNational Research Centre
KeywordsCannabisPandemicCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Substance useEnvironmental health2019-20 coronavirus outbreakGeographyVirologyBiologyMedicinePsychiatryInternal medicineOutbreak

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.228
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.305
GPT teacher head0.462
Teacher spread0.157 · 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

Citations7
Published2021
Admission routes1
Has abstractno

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