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Cytodiagnosis of bronchogenic carcinoma and neuroendocrine tumor of the lung by transthoracic fine-needle aspiration

2000· article· en· W1994568470 on OpenAlexaff
Gia‐Khanh Nguyen, J. Gray, Eric Wong, Jennifer A. Crocket, Ciaran McNamee

Bibliographic record

VenueDiagnostic Cytopathology · 2000
Typearticle
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsUniversity of Alberta Hospital
Fundersnot available
KeywordsMedicineBronchogenic carcinomaNeuroendocrine carcinomaLungCarcinomaFine-needle aspirationRadiologySmall Cell Lung CarcinomaNeuroendocrine tumorsPathologyInternal medicineSmall-cell carcinomaBiopsy

Abstract

fetched live from OpenAlex

To evaluate our experience with the cytodiagnosis of primary lung cancers by transthoracic fine-needle aspiration (TFNA), 106 bronchogenic carcinomas (BC) and 6 neuroendocrine tumors of the lung (NTL) with adequate needle aspirates were reviewed. The cytodiagnostic accuracy rates of BCs were 75.5%, 72%, 100%, 53%, and 50% for bronchogenic adenocarcinomas, squamous-cell carcinomas, small-cell carcinomas, large-cell carcinomas, and mixed carcinomas, respectively. Of the 6 NTLs, 4 typical carcinoid tumors (CT) were correctly diagnosed, 1 atypical CT was wrongly identified as small-cell carcinoma, and 1 large-cell NTL was mistaken for an adenocarcinoma.

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.

How this classification was reachedexpand

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)0.000
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 score0.198
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.000
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 head0.008
GPT teacher head0.270
Teacher spread0.261 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2000
Admission routes1
Has abstractyes

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