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Record W2141335977 · doi:10.1037/1064-1297.12.1.3

Intra-Administration Associations and Withdrawal Symptoms: Morphine-Elicited Morphine Withdrawal.

2004· article· en· W2141335977 on OpenAlexaff
Robert V. McDonald, Shepard Siegel

Bibliographic record

VenueExperimental and Clinical Psychopharmacology · 2004
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsMcMaster University
FundersNational Institute on Drug Abuse
KeywordsMorphineDrug withdrawalMedicineDrugOpiateAnesthesiaDrug administrationKindlingSelf-administrationPsychologyPharmacologyInternal medicineStimulationReceptor

Abstract

fetched live from OpenAlex

On the basis of a conditioning analysis, some drug "withdrawal symptoms" are conditional responses elicited by stimuli paired with the drug effect. Prior demonstrations of conditional elicitation of withdrawal symptoms evaluated the role of environmental cues; however, pharmacological cues also typically signal a drug effect. Within each administration, early drug onset cues (DOCs) may become associated with the later, larger drug effect (intra-administration associations). This experiment evaluated the contribution of intra-administration associations to withdrawal symptoms. The results indicated that (a). 5 mg/kg morphine elicited behavioral and thermic withdrawal symptoms in rats previously injected on a number of occasions with 50 mg/kg morphine and that (b). DOC-elicited withdrawal symptoms are not a sensitized response to the opiate but rather an associative phenomenon.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.390
Teacher spread0.359 · 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 source (direct Gemma or distilled Codex), 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

Citations38
Published2004
Admission routes1
Has abstractyes

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