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Record W4362602027 · doi:10.1002/jca.22043

Guidelines on the Use of Therapeutic Apheresis in Clinical Practice – Evidence‐Based Approach from the Writing Committee of the American Society for Apheresis: The Ninth Special Issue

2023· article· en· W4362602027 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Apheresis · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsApheresisNinthMedicineGrading (engineering)Intensive care medicineMedical educationImmunologyEngineering

Abstract

fetched live from OpenAlex

The American Society for Apheresis (ASFA) Journal of Clinical Apheresis (JCA) Special Issue Writing Committee is charged with reviewing, updating, and categorizing indications for the evidence-based use of therapeutic apheresis (TA) in human disease. In the Ninth Edition, the JCA Special Issue Writing Committee has incorporated systematic review and evidence-based approaches in the grading of evidence and categorization of apheresis indications to make recommendations on the use of apheresis in a wide variety of diseases and conditions. This edition has largely maintained the general layout and concept of a fact sheet introduced in the Fourth Edition (2007). Each fact sheet succinctly summarizes the evidence for the use of TA in a specific disease or medical condition. The Ninth Edition of the JCA Special Issue comprises 91 fact sheets and 166 graded and categorized indications. This includes seven new fact sheets, nine new indications on existing fact sheets, and eight changes in the category for existing indications. The Ninth Edition of the JCA Special Issue seeks to continue to serve as a key resource that guides the utilization of TA in the treatment of human disease.

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)0.014
metaresearch head score (Gemma)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.494
GPT teacher head0.490
Teacher spread0.004 · 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