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Record W4402548066 · doi:10.1111/vox.13737

Correction to ‘Determining the impact of current Canadian stem cell registry policy on donor availability via dynamic registry simulation’

2024· erratum· en· W4402548066 on OpenAlexaboutno aff

Bibliographic record

VenueVox Sanguinis · 2024
Typeerratum
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineComputer scienceFamily medicineOperations researchEngineering

Abstract

fetched live from OpenAlex

Blake J, Kanz G, Seftel MD, Allan D. Determining the impact of current Canadian stem cell registry policy on donor availability via dynamic registry simulation. Vox Sang. 2024;119:598–605. http://doi.org/10.1111/vox.13619 In paragraph 2 of the ‘Non-Caucasian searches at historic rates (Patient Case P1)’ section, the text ‘Simulated patients were matched with simulated patients, assuming that the CBSSCR dynamically evolves over time’ was incorrect. This should have read: ‘Simulated patients were matched with simulated donors, assuming that the CBSSCR dynamically evolves over time’. We apologize for this error.

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)0.008
metaresearch head score (Gemma)0.157
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.906
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.157
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0050.002
Open science0.0040.002
Research integrity0.0090.015
Insufficient payload (model declined to judge)0.0640.043

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 head0.020
GPT teacher head0.338
Teacher spread0.318 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2024
Admission routes1
Has abstractyes

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