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Record W2778176950 · doi:10.1002/cyto.b.21615

ICCS/ESCCA Consensus Guidelines to detect GPI‐deficient cells in Paroxysmal Nocturnal Hemoglobinuria (PNH) and related Disorders Part 4 – Assay Validation and Quality Assurance

2017· article· en· W2778176950 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

VenueCytometry Part B Clinical Cytometry · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsCaprion (Canada)
Fundersnot available
KeywordsParoxysmal nocturnal hemoglobinuriaQuality assuranceFlow cytometryMedicineMedical physicsComputer scienceImmunologyPathologyExternal quality assessment

Abstract

fetched live from OpenAlex

Over the past six years, a diverse group of stakeholders have put forth recommendations regarding the analytical validation of flow cytometric methods and described in detail the differences between cell-based and traditional soluble analyte assay validations. This manuscript is based on these general recommendations as well as the published experience of experts in the area of PNH testing. The goal is to provide practical assay-specific guidelines for the validation of high-sensitivity flow cytometric PNH assays. Examples of the reports and validation data described herein are provided in Supporting Information. © 2017 International Clinical Cytometry Society.

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)0.007
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.103
GPT teacher head0.410
Teacher spread0.306 · 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