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Record W3206184344 · doi:10.2196/33891

Correction: Electronic Video Consent to Power Precision Health Research: A Pilot Cohort Study

2021· erratum· en· W3206184344 on OpenAlexvenueno aff
Arash Naeim, Sarah Dry, David Elashoff, Zhuoer Xie, Antonia Petruse, Clara E. Magyar, Liliana Johansen, Gabriela Werre, Clara Lajonchere, Neil S. Wenger

Bibliographic record

VenueJMIR Formative Research · 2021
Typeerratum
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceCohortCohort studyPower (physics)Informed consentMedical physicsMedicinePsychologyMedical educationAlternative medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

[This corrects the article DOI: 10.2196/29123.].

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)0.025
metaresearch head score (Gemma)0.362
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.103
Threshold uncertainty score0.343

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.362
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.003
Science and technology studies0.0060.004
Scholarly communication0.0060.004
Open science0.0040.003
Research integrity0.0090.012
Insufficient payload (model declined to judge)0.1030.039

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 head0.588
GPT teacher head0.657
Teacher spread0.069 · 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 designObservational
Domainnot available
GenreOther

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

Citations3
Published2021
Admission routes1
Has abstractyes

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