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Record W4292714772 · doi:10.51731/cjht.2022.425

Reflections on the Canadian Bleeding Disorders Registry: Lessons Learned and Future Perspectives

2022· article· en· W4292714772 on OpenAlex
Alfonso Iorio, Sylvain Grenier, David L. Page, Arun Keepanasseril, Emma Iserman, Jean‐Éric Tarride, Davide Matino, Jayson Stoffman, Jerome Teitel, Lorraine Boyle

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Health Technologies · 2022
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementDiseaseModalitiesMedicineEpidemiologyProduct (mathematics)Family medicineIntensive care medicineBusinessPathologySociology

Abstract

fetched live from OpenAlex


 The Canadian Bleeding Disorders Registry (CBDR) has become the national registry for comprehensive care and research in hemophilia in Canada with patient, clinical, and research module connectivity.
 The CBDR has served as a robust resource to inform epidemiology of disease, burden of disease, and disease changes and variation over time as new treatment modalities are introduced.
 Information on the utilization of blood products to treat hemophilia has and can be retrieved and used by Canadian blood product procurement agencies to inform decision-making for past and future purchases.
 The successful multistakeholder coordination and alignment achieved over decades with the development and function of the CBDR is an exemplar that could be extended to other rare disease areas.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.110
GPT teacher head0.402
Teacher spread0.292 · 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