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Record W4388941407 · doi:10.3389/fpain.2023.1330531

Editorial: Perspectives on music and pain: from evidence to theory and application

2023· editorial· en· W4388941407 on OpenAlexafffund
Annabel J. Cohen, Andrea McGraw Hunt, Eduardo A. Garza‐Villarreal, Xuejing Lu

Bibliographic record

VenueFrontiers in Pain Research · 2023
Typeeditorial
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsUniversity of Prince Edward Island
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsVolume (thermodynamics)PsychologyMedicinePhysics

Abstract

fetched live from OpenAlex

EDITORIAL article Front. Pain Res., 23 November 2023Sec. Pain Mechanisms Volume 4 - 2023 | https://doi.org/10.3389/fpain.2023.1330531

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)0.008
metaresearch head score (Gemma)0.028
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0060.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0050.002
Science and technology studies0.0040.002
Scholarly communication0.0070.005
Open science0.0040.002
Research integrity0.0170.016
Insufficient payload (model declined to judge)0.0260.017

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 head0.069
GPT teacher head0.436
Teacher spread0.367 · 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
GenreEditorial

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

Citations2
Published2023
Admission routes2
Has abstractyes

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