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Sham Surgeries: Have We Gone Too Far?

2010· article· en· W2012711733 on OpenAlexaff
Victor K. Y. Wu, Mohit Bhandari

Bibliographic record

VenueEthics in Biology Engineering and Medicine An International Journal · 2010
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsHamilton General HospitalMcMaster University
Fundersnot available
KeywordsPlaceboHarmTransparency (behavior)Research ethicsRandomized controlled trialIntervention (counseling)MedicinePsychologyClinical equipoiseClinical trialAlternative medicineSocial psychologySurgeryNursingPolitical scienceLawPsychiatry

Abstract

fetched live from OpenAlex

The use of placebo surgeries can be ethically justified under certain conditions depending on the current state of evidence existing for surgical procedures, methodological considerations of the randomized controlled trial (RCT), and the welfare of research participants. It may be impossible to eliminate all risks associated with placebo surgery, but the mitigation of risk has moral weight and is already practiced outside of health research. If ethics is a reflection of social and cultural values of the society in which it operates, one can reasonably conclude that certain placebo procedures can be used in surgical RCTs. However, in situations whereby quality of life is irrevocably lost, as in the case of placebo procedures that directly or indirectly invoke serious and irreversible harm, the undertaking of such a trial would be inappropriate. Research ethics boards (REBs) may play a role in research involving placebo surgery by: i) ensuring clinical equipoise between intervention and placebo treatments; ii) increasing transparency between the research ethics board, the researcher, and the participant; and iii) ensuring that adequate time is given for the individual to contemplate participation.

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)0.081
metaresearch head score (Gemma)0.152
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.081
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0810.152
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0030.028
Scholarly communication0.0070.020
Open science0.0030.004
Research integrity0.0130.017
Insufficient payload (model declined to judge)0.0150.004

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 head0.381
Teacher spread0.321 · 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
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

Citations0
Published2010
Admission routes1
Has abstractyes

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Same venueEthics in Biology Engineering and Medicine An International JournalSame topicPain Management and Placebo EffectFrench-language works237,207