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Record W4320716061 · doi:10.1016/j.eclinm.2023.101852

Letter to Editor-response: placebo response rates

2023· letter· en· W4320716061 on OpenAlexafffund
Bishal Gyawali

Bibliographic record

VenueEClinicalMedicine · 2023
Typeletter
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsQueen's University
FundersGovernment of OntarioOntario Institute for Cancer Research
KeywordsMedicinePlaceboPlacebo responseClinical trialInternal medicineRandomized controlled trialOncologyPathologyAlternative medicine

Abstract

fetched live from OpenAlex

We'd like to thank van der Graaf et al. for their thoughtful comments and feedback on our article analyzing the response rate from placebo in cancer drug clinical trials.1 The overall response rate from placebo was 1% across the trials that included multiple cancer histology. Subgroup analysis revealed a higher response rate of 4% in sarcoma trials. Van der Graaf et al. are correct that this was affected predominantly by the high placebo response seen in the trial by Gounder et al. in desmoid tumors, an explanation that has been included in the updated version of the article.

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)0.004
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.013

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 head0.058
GPT teacher head0.385
Teacher spread0.327 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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