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Drug Tolerance, Drug Addiction, and Drug Anticipation

2005· article· en· W2131845441 on OpenAlexaff
Shepard Siegel

Bibliographic record

VenueCurrent Directions in Psychological Science · 2005
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAddictionPsychologyDrug withdrawalDrugAnticipation (artificial intelligence)Drug toleranceSensory cueCognitionClassical conditioningConditioningCognitive psychologyNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

Environmental cues associated with drugs often elicit withdrawal symptoms and relapse to drug use. Such cues also modulate drug tolerance. The contribution of drug-associated stimuli to withdrawal and tolerance is emphasized in a Pavlovian-conditioning analysis of drug administration. Conditional responses occur in the presence of cues that have been associated with the drug in the past, such as the setting in which the drug was taken. These conditional responses mediate the expression of tolerance and withdrawal symptoms. Recently, it has become apparent that internal predrug cues, as well as environmental cues, elicit pharmacological conditional responses that contribute to tolerance and withdrawal. Such internal cues include cognitive or proprioceptive cues incidental to self-administration, drug-onset cues that are experienced shortly after administration, and emotional cues. According to the conditioning analysis, addiction treatment should incorporate learning principles to extinguish the association between stimuli (environmental and internal) present at the time of drug administration and the effects of the addictive drug.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
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 head0.098
GPT teacher head0.415
Teacher spread0.318 · 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 designBench or experimental
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

Citations108
Published2005
Admission routes1
Has abstractyes

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