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Record W4205552637 · doi:10.1002/rth2.12554

Abstract

2021· article· en· W4205552637 on OpenAlexaff
Kelly Bajorek, Tarango, Jones, Martin, Palumbo, Lori Luchtman‐Jones, Taha Bat, Maguire, Ekrem Turk, Becker, Catalfamo, Wang, Kisha A Beg, C Toohey, Song Chen, Janna M. Journeycake, Osman Khan, Herbert L. Bonkovsky, Langendonk, Balwani, Sardh, Gouya, Rees, Stein, Stölzel, Peiro, Bissell, Keel, Parker, Silver, Windyga, D'avola, Ross, Steward, Ritchie, Oh, Harper, Ianova, Horie, Anderson, Elisabeth I. Minder, Vassiliou, Kubisch, E Guillen-Navaro, Coman, Goto, Jonathan M. Ducore, Mancuso, Simpson, Holme, Enriquez, Reding

Bibliographic record

VenueResearch and Practice in Thrombosis and Haemostasis · 2021
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of Alberta
FundersBarts and The London School of Medicine and DentistryAmsterdam University Medical CentersProvincie West-VlaanderenNational Health Laboratory ServiceErasmus Universitair Medisch Centrum RotterdamAnschutz Medical Campus, University of ColoradoRigshospitaletChildren's Healthcare of AtlantaUniversity of South FloridaVlaamse regeringUniversiteit van AmsterdamCentral Michigan UniversityUniversity of Texas Health Science Center at HoustonUniversity of CambridgeVanderbilt University Medical CenterUniversity of Arkansas for Medical SciencesVanderbilt UniversityUniversity of California, San DiegoUniversity Hospital Southampton NHS Foundation TrustUniversity of North Carolina at Chapel HillUniversitair Medisch Centrum GroningenAflacEmory UniversityChildren's Hospital Los AngelesUniversity of Southern California
KeywordsComputer science

Abstract

fetched live from OpenAlex

The Pediatric Bleeding Questionnaire (PBQ) is a validated bleeding assessment tool to standardize history-taking and distinguish those with mild-moderate bleeding disorders; however,

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.917
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0830.027

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 head0.230
GPT teacher head0.482
Teacher spread0.252 · 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.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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