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Record W2012242609 · doi:10.1309/5vtrreujw9ladrgt

Equivalence of Laser Scanning Cytometric and Flow Cytometric Immunophenotyping of Lymphoid Lesions in Cytologic Samples

2008· article· en· W2012242609 on OpenAlex
Ali Mohammed Al-Za’abi, William Geddie, Scott Boerner

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 · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsImmunophenotypingPathologyFlow cytometryCytometryPopulationBiologyCytologyImmunologyMedicine

Abstract

fetched live from OpenAlex

The immunophenotype of lymphoid cytologic samples obtained by laser scanning cytometry (LSC) and flow cytometry (FC) was compared in 72 cases composed of a series of 23 cases with simultaneous LSC and FC immunophenotyping and a second series of 49 cases in which nonsimultaneous immunophenotyping was performed. In both series, no discordance in the population immunophenotype was found that would result in changes in diagnostic classification, although minor discordance in some antigens was found, predominantly affecting FMC7, CD11c, and CD23. The immunophenotype obtained by LSC shows a high degree of concordance with that obtained by FC and generates results that are diagnostically equivalent. Potential explanations for the discordant markers include differences related to the techniques, differences in the fluorochrome-labeled antibodies, technical factors, differences in antigen expression related to anatomic sites, temporal variations, and interpretive variances.

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)0.003
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 score0.205
Threshold uncertainty score0.515

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.070
GPT teacher head0.341
Teacher spread0.271 · 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