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Record W6963999909 · doi:10.25384/sage.23699908

sj-docx-1-tab-10.1177_1759720X231182894 – Supplemental material for Mechanisms hypothesized for pain-relieving effects of exercise in fibromyalgia: a scoping review

2023· article· en· W6963999909 on OpenAlexaff

Bibliographic record

VenueSage Journals Data · 2023
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDiseasePhysical exercisePhysical activityExercise physiologyMEDLINE

Abstract

fetched live from OpenAlex

Supplemental material, sj-docx-1-tab-10.1177_1759720X231182894 for Mechanisms hypothesized for pain-relieving effects of exercise in fibromyalgia: a scoping review by Yuva Venkata Raghava Neelapala, Domenico Mercuri, Luciana Macedo, Steven Hanna, Dylan Kobsar and Lisa Carlesso in Therapeutic Advances in Musculoskeletal Disease

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)0.003
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.944
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.043
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0100.014
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.9440.581

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 head0.060
GPT teacher head0.371
Teacher spread0.310 · 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.

Study designSystematic review
Domainnot available
GenreDataset

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

Citations0
Published2023
Admission routes1
Has abstractyes

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