MétaCan
Menu
Back to cohort
Record W3161344260 · doi:10.1002/sctm.20-0428

Ethical issues concerning a pay-to-participate stem cell study

2021· article· en· W3161344260 on OpenAlexaff
Leigh Turner, Jeremy Snyder

Bibliographic record

VenueStem Cells Translational Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsConflict of interestContext (archaeology)PaymentStem cellDonationPsychological interventionScientific integrityPublic relationsBusinessPolitical scienceMedicineEngineering ethicsFinanceLaw

Abstract

fetched live from OpenAlex

In our critique of a pay-to-participate study, we address how the failure to disclose study-related payments appears to have violated STEM CELLS Translational Medicine's editorial policies concerning conflict-of-interest and financial disclosure. Our analysis also identifies broader ethical issues and scientific concerns related to pay-to-participate studies conducted by businesses with a record of selling purported stem cell treatments before determining whether the products they sell are safe and efficacious. Authors of peer-reviewed articles have a responsibility to comply with journal policies and disclose financial conflicts of interest to editors, reviewers, and readers. Authors should also disclose when stem cell interventions being tested in clinical trials have already been sold on a direct-to-consumer basis as "stem cell treatments" by authors' affiliate institutions. Financial conflicts of interest and other forms of possible bias must be disclosed to put clinical studies in context and facilitate the critical assessment of research methods, findings, and conclusions. The apparent failure to comply with journal editorial policies and disclose such financial conflicts warrants careful investigation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.504
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.360
Teacher spread0.286 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations15
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueStem Cells Translational MedicineSame topicBiomedical Ethics and RegulationFrench-language works237,207