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Record W1698167416 · doi:10.1177/0163278702238052

The Biochemical Bases for Reward

2002· article· en· W1698167416 on OpenAlexaff
Raúl de la Fuente‐Fernández, A. Jon Stoessl

Bibliographic record

VenueEvaluation & the Health Professions · 2002
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNucleus accumbensPlaceboDopamineAddictionMedicineOpioidNeurosciencePsychologyPharmacologyMechanism (biology)PsychiatryInternal medicine

Abstract

fetched live from OpenAlex

The authors propose that the placebo effect is mediated by reward-related mechanisms. Recent evidence suggests that it is the expectation of reward (in this case, the expectation of clinical benefit) that triggers the placebo response. In Parkinson's disease, the placebo effect is mediated by the release of dopamine in the striatum. The authors argue that placebo-induced dopamine release in limbic structures, particularly in the nucleus accumbens, could also be a major biochemical substrate for the placebo effect encountered in other medical disorders. Other neuroactive substances involved in the reward circuitry (e.g., opioids) are also likely to contribute to the placebo response, and such contribution may be disorder specific (e.g., opioid release in placebo analgesia; serotonin regulation in response to placebo antidepressants). In addition, placebos may have a role in substitution programs for the treatment of drug addiction.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.006
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.309
GPT teacher head0.453
Teacher spread0.144 · 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

Citations55
Published2002
Admission routes1
Has abstractyes

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