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Record W2145743905 · doi:10.1101/cshperspect.a012096

The Neurobiology of Opiate Motivation

2012· review· en· W2145743905 on OpenAlexaff
Ryan Ting‐A‐Kee, Derek van der Kooy

Bibliographic record

VenueCold Spring Harbor Perspectives in Medicine · 2012
Typereview
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsOccupational Cancer Research CentreUniversity of TorontoOntario Institute for Cancer Research
Fundersnot available
KeywordsVentral tegmental areaDopamineNeuroscienceOpiateAddictionDopamine receptorPsychologyReward systemMedicineReceptorDopaminergicInternal medicine

Abstract

fetched live from OpenAlex

Opiates are a highly addictive class of drugs that have been reported to possess both dopamine-dependent and dopamine-independent rewarding properties. The search for how, if at all, these distinct mechanisms of motivation are related is of great interest in drug addiction research. Recent electrophysiological, molecular, and behavioral work has greatly improved our understanding of this process. In particular, the signaling properties of GABA(A) receptors located on GABA neurons in the ventral tegmental area (VTA) appear to be crucial to understanding the interplay between dopamine-dependent and dopamine-independent mechanisms of opiate motivation.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.366
Teacher spread0.240 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations63
Published2012
Admission routes1
Has abstractyes

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