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Record W2783117720 · doi:10.1111/adb.12592

Validation of a behavioral economic purchase task for assessing drug abuse liability

2018· article· en· W2783117720 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAddiction Biology · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
FundersNational Institute on Drug AbuseNational Institutes of Health
KeywordsAbuse liabilityDrugPlaceboAmphetamineLiabilityPsychologyStimulantBehavioral economicsTask (project management)Substance abuseMedicinePsychiatryBusinessEconomicsNeuroscienceMicroeconomicsAlternative medicine

Abstract

fetched live from OpenAlex

Abstract Behavioral economic purchase tasks quantify drug demand (i.e. reinforcing value of a drug) and have been used extensively to assess the value of various drugs among current users. However, purchase tasks have been rarely used with unfamiliar drugs to address a compound's abuse liability, and the current study sought to validate the paradigm in this capacity. Using a double‐blind placebo‐controlled within‐subjects drug challenge design, the study evaluated differential drug demand on an experimental drug purchase task for a 20 mg dose of oral D‐amphetamine (versus placebo), a prototypic psychostimulant, in 98 stimulant‐naïve participants. Compared with placebo, amphetamine significantly increased intensity, breakpoint and O max , and significantly decreased elasticity. Mechanistic analyses revealed that O max and breakpoint mediated the relationship between subjective drug effects and ‘ willingness to take again ’, a putative indicator of liability via motivation for future drug‐seeking behavior. These findings validate the purchase task paradigm for quantifying the reinforcing value and, in turn, abuse liability of unfamiliar compounds, providing a foundation for a variety of future applications.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.126
GPT teacher head0.419
Teacher spread0.292 · 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