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Record W4411201921 · doi:10.2196/78781

Correction: ENABLE—App-Based Digital Capture and Intervention of Patient-Reported Quality of Life, Adverse Events, and Treatment Satisfaction in Breast Cancer: Protocol for a Randomized Controlled Trial

2025· erratum· en· W4411201921 on OpenAlexaffvenue
Thomas M. Deutsch, Léa L Volmer, Manuel Feißt, Laura Bodenbeck, Kathrin Haßdenteufel, Lara Tretschock, Christiane Breit, S Stefanovic, A. Bauer, Carolin Anders, Lina Weinert, Tobias Engler, Andreas D. Hartkopf, Nico Pfeifer, Marc Mausch, Oliver Heinze, Marc Sütterlin, Sara Y. Brucker, Andreas Schneeweiß, Markus Wallwiener

Bibliographic record

VenueJMIR Research Protocols · 2025
Typeerratum
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsProtocol (science)Randomized controlled trialIntervention (counseling)Quality of life (healthcare)Breast cancerMedicineAdverse effectPatient satisfactionAlternative medicineMedical physicsCancerComputer scienceNursingInternal medicine

Abstract

fetched live from OpenAlex

[This corrects the article DOI: 10.2196/69855.].

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)0.030
metaresearch head score (Gemma)0.277
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.268
Threshold uncertainty score0.896

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.277
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0030.002
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.2680.043

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 head0.085
GPT teacher head0.432
Teacher spread0.347 · 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 designRandomized trial
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

Citations0
Published2025
Admission routes2
Has abstractyes

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