MétaCan
Menu
Back to cohort
Record W2795771146 · doi:10.5858/arpa.2017-0167-cp

Performance Characteristics of Cerebrospinal Fluid Cytology: An Analysis of Responses From the College of American Pathologists Nongynecologic Cytopathology Education Program

2018· article· en· W2795771146 on OpenAlex
Z. Laura Tabatabai, Manon Auger, Rhona J. Souers, Lisa A. Teot, Diane D. Davey

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

VenueArchives of Pathology & Laboratory Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicLymphadenopathy Diagnosis and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsCytopathologyConcordanceMedicineCytologyCerebrospinal fluidPathologyLymphomaMedical diagnosisLeukemiaMalignancyInternal medicine

Abstract

fetched live from OpenAlex

CONTEXT: - Cerebrospinal fluid cytology is a critical diagnostic tool for the diagnosis of many conditions affecting the central nervous system. OBJECTIVE: - To assess the performance characteristics of cerebrospinal fluid cytology samples by evaluating participant interpretations within the College of American Pathologists Nongynecologic Cytopathology Education program. DESIGN: - Participant interpretations (N = 46 264) evaluated in the College of American Pathologists Nongynecologic Cytopathology Education Program were examined for concordance with the general category and with the reference diagnosis. Two nonlinear mixed models were used to analyze the concordance rates. RESULTS: - The overall concordance rates for the general category and reference diagnosis were 92.1% and 81.0%, respectively. In the malignant category, the concordance rates with the reference diagnosis were lowest for diagnoses of nonhematopoietic small blue round cell tumors (54.8%) and metastatic malignancy (77.5%); the concordance rate with the reference diagnosis was highest for leukemia/lymphoma (94.0%). In the benign category, the concordance rate was lowest for normal cerebrospinal fluid reference diagnoses (58.6%), followed by acute and chronic inflammation (64.6%), fungal infection (80.8%), and macrophages (85.3%). Significant differences in concordance were uncovered when performance was evaluated by participant type and stain technique. Leukemia/lymphoma was the most common diagnosis for misclassified nonhematopoietic small blue round cell tumor cases and negative or inflammatory cerebrospinal fluid cases. CONCLUSIONS: - This study illustrates the difficulties in achieving accurate diagnoses from cerebrospinal fluid specimens, particularly for nonhematopoietic small blue round cell tumors and normal and inflammatory cerebrospinal fluid specimens.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.009
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 head0.014
GPT teacher head0.315
Teacher spread0.301 · 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