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Record W3024847612 · doi:10.1111/vox.12902

Vox Sanguinis International forum on the selection and preparation of blood components for intrauterine transfusion

2020· article· en· W3024847612 on OpenAlexaff
Melanie Bodnar, Miquel Lozano, Veera Sekaran Nadarajan, Christina Lee, David Baud, Giorgia Canellini, Tobias Gleich‐Nagel, Oscar Walter Torres, Patricia L. Rey, Carolina Bonet Bub, José Mauro Kutner, Lilian Castilho, Nabiha H. Saifee, Meghan Delaney, Theresa Nester, Agneta Wikman, Eleonor Tiblad, Luca Pierelli, Antonella Matteocci, Maddalena Maresca, Émeline Maisonneuve, A. Cortey, Jean‐Marie Jouannic, Jordi Fornells, Arjan Albersen, Masja de Haas, Dick Oepkes, Lani Lieberman

Bibliographic record

VenueVox Sanguinis · 2020
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsCanadian Blood ServicesUniversity of Alberta
Fundersnot available
KeywordsBlood transfusionMedicineSelection (genetic algorithm)Intensive care medicineComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Indication for

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)0.004
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.039
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0390.014

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 head0.026
GPT teacher head0.280
Teacher spread0.254 · 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
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

Citations6
Published2020
Admission routes1
Has abstractyes

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