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Record W2077910494 · doi:10.1111/hae.12511

Answering relevant research questions via careful observation of clinical practice: a fresh look at the old way forward

2014· letter· en· W2077910494 on OpenAlexaff
Davide Matino, Alfonso Iorio

Bibliographic record

VenueHaemophilia · 2014
Typeletter
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineClinical PracticeClass (philosophy)Product (mathematics)Medical educationFamily medicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Although many aspects of inhibitor development have been elucidated, the role of switching FVIII product concentrate in the risk of inhibitors development in previously treated patients is still under discussion. To provide their contribution, Aznar et al [9] transparently showed the numerous different brands used over time and the number of patients treated with one or another class of concentrates in their center. This way of inclusively reporting data as generated in routine clinical practice would need to be adopted more broadly among hemophilia treater and scientists. Strength and limitations of the approach are discussed.

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)0.091
metaresearch head score (Gemma)0.264
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.909
Threshold uncertainty score0.483

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0910.264
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0050.020
Scholarly communication0.0140.045
Open science0.0050.007
Research integrity0.0460.077
Insufficient payload (model declined to judge)0.0050.004

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 head0.165
GPT teacher head0.447
Teacher spread0.283 · 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 designTheoretical or conceptual
DomainMethods
GenreCommentary

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
Published2014
Admission routes1
Has abstractyes

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