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Record W2081307885 · doi:10.1172/jci77193

A brain network response to sham surgery

2014· letter· en· W2081307885 on OpenAlexafffund
Mariya V. Cherkasova, A. Jon Stoessl

Bibliographic record

VenueJournal of Clinical Investigation · 2014
Typeletter
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsUniversity of British Columbia
FundersParkinsonfondenCanada Research ChairsCanadian Institutes of Health ResearchNational Parkinson FoundationFondation pour la Recherche sur AlzheimerMichael J. Fox Foundation for Parkinson's Research
KeywordsMedicineNeuroscienceBioinformaticsPsychologyBiology

Abstract

fetched live from OpenAlex

Evaluation of potential therapies for neurological disease has been challenging due to beneficial responses in patients receiving the sham/placebo treatment. Placebo effects are especially prominent in Parkinson's disease (PD), which has become a useful model for studying the neurobiology of placebo responses. In this issue of the JCI, Ko and colleagues identify a neural circuit associated with the placebo response in a PD patient cohort. The observed placebo effect-associated pattern involved metabolic activity increases that corresponded with long-term motor improvements after sham surgery. Presurgery activity in this network was inversely related to sham response, suggesting that this network has potential for identifying sham responders and thus reducing placebo-related variance in surgical trials.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.062
metaresearch head score (Gemma)0.183
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.121
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0620.183
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.183
GPT teacher head0.389
Teacher spread0.206 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations16
Published2014
Admission routes2
Has abstractyes

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