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Record W3015191949 · doi:10.32598/bcn.11.covid19.1

COVID-19 and Substance Use Disorders as Brain Diseases: Recommendations to a Comprehensive Healthcare Response. An International Society of Addiction Medicine (ISAM) Practice and Policy Interest Group Position Paper

2020· article· en· W3015191949 on OpenAlexaff
Ali Farhoudian, Alex Baldacchino, Nicolas Clark, Gilberto Gerra, Hamed Ekhtiari, Geert Dom, Azarakhsh Mokri, Mandana Sadeghi, Pardis Nematollahi, Maryanne Demasi, Christian Schütz, Seyed Mohammadreza Hashemian, Payam Tabarsi, Susanna Galea-Singer, Giuseppe Carrà, Thomas Clausen, Christos Kouimtsidis, Serenella Tolomeo, Seyed Ramin Radfar, Emran Mohammad Razaghi

Bibliographic record

VenueBasic and Clinical Neuroscience Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of British Columbia
FundersUniversity of California, Los AngelesYale University
KeywordsAddictionPosition paperSubstance useAddiction medicineCoronavirus disease 2019 (COVID-19)Health carePosition (finance)Healthcare policyMedicinePsychiatryPsychologyPolitical scienceHealth policyInternational healthBusinessPathologyLaw

Abstract

fetched live from OpenAlex

Coronavirus Disease 2019 (COVID-19) is escalating all over the world and has higher morbidities and mortalities in certain vulnerable populations. People Who Use Drugs (PWUD) are a marginalized and stigmatized group with weaker immunity responses, vulnerability to stress, poor health conditions, high-risk behaviors, and lower access to health care services. These conditions put them at a higher risk of COVID-19 infection and its complications. In this paper, an international group of experts on addiction medicine, infectious diseases, and disaster psychiatry explore the possible raised concerns in this issue and provide recommendations to manage the comorbidity of COVID-19 and Substance Use Disorder (SUD).

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)0.005
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 score0.343
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.217
GPT teacher head0.531
Teacher spread0.314 · 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

Citations100
Published2020
Admission routes1
Has abstractyes

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