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Record W2806934311 · doi:10.1177/0963689718755708

Better to be in The Placebo Arm for Trials of Neurological Therapies?

2018· article· en· W2806934311 on OpenAlex
Jonathan Kimmelman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCell Transplantation · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcGill University
Fundersnot available
KeywordsPlaceboMedicineClinical trialAdverse effectAlternative medicineRandomizationNeurologyPhysical therapyInternal medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

Patients with progressive neurodegenerative diseases often pursue trial entry seeking to access cutting edge therapies. However, cutting edge therapies for neurodegenerative diseases tend to have higher adverse event rates and underperform placebo. This essay argues that patients seeking trial entry are probably better off, medically, by being assigned to the placebo arm. Because trials involve extra clinic visits and research procedures, patients may be still better off medically by skipping trial participation altogether. I close by arguing that the Neurology research community might better honor the contributions of research subjects by pressing sponsors to promptly publish the results of non-positive trials, minimizing the use of uneven randomization ratios that favor assignment to the investigational treatment, and by fostering systematic collection of data on the risk/benefit balance of trial 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.

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)0.019
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.471
GPT teacher head0.444
Teacher spread0.027 · 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