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Record W2134190275 · doi:10.1309/ajcpmrdzzfqm7yj4

Use of a FLAER-Based WBC Assay in the Primary Screening of PNH Clones

2009· article· en· W2134190275 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

VenueAmerican Journal of Clinical Pathology · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsLondon Health Sciences CentreUniversity Health Network
Fundersnot available
KeywordsParoxysmal nocturnal hemoglobinuriaclone (Java method)Flow cytometryAplastic anemiaImmunologyCD59CD33HemolysisCD64Molecular biologyMedicineBiologyAntibodyGeneticsStem cellCD34GeneBone marrow

Abstract

fetched live from OpenAlex

Diagnosis of paroxysmal nocturnal hemoglobinuria (PNH) with flow cytometry traditionally involves the analysis of CD55 and CD59 on RBCs and neutrophils. However, the ability to accurately detect PNH RBCs is compromised by prior hemolysis and/or transfused RBCs. Patients with aplastic anemia (AA) and myelodysplastic syndrome (MDS) can also produce PNH clones. We recently described a multiparameter fluorescent aerolysin (FLAER)-based flow assay using CD45, CD33, and CD14 that accurately identified PNH monocyte and neutrophil clones in PNH, AA, and MDS. Here, we compared the efficiency of this WBC assay with a CD59-based assay on RBCs during a 3-year period. PNH clones were detected with the FLAER assay in 63 (11.8%) of 536 samples tested, whereas PNH RBCs were detected in only 33 (6.2%), and always with a smaller clone size. The FLAER assay on WBCs is a more sensitive and robust primary screening assay for detecting PNH clones in clinical samples.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.097
GPT teacher head0.383
Teacher spread0.286 · 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