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Record W2062802492 · doi:10.1002/dc.20662

Cyto‐histological correlations in primary, recurrent and metastatic rhabdomyosarcoma: The institut Curie's experience

2007· article· en· W2062802492 on OpenAlexaff
Jerzy Klijanienko, Jean‐Michel Caillaud, Daniel Orbach, Hervé J. Brisse, Réal Lagacé, Philippe Vielh, Jérôme Couturier, Paul Fréneaux, Stamatios Theocharis, Xavier Sastre‐Garau

Bibliographic record

VenueDiagnostic Cytopathology · 2007
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsHôtel-Dieu de Québec
Fundersnot available
KeywordsMedicineRhabdomyosarcomaCytologyAtypiaPathologyAlveolar rhabdomyosarcomaFine-needle aspirationMultinucleateGiant cellSarcomaCytopathologyBiopsy

Abstract

fetched live from OpenAlex

To determine diagnostic cytomorphologic features of rhabdomyosarcoma (RMS) on fine-needle aspiration (FNA) material, the cytologic material and corresponding histologic slides of 180 tumors obtained from 109 patients were reviewed. Fifty eight (32.2%) tumors were primary, 34 (18.9%) recurrent, and 88 (48.9%) metastatic. A review of original cytology reports revealed that 176 of 180 (97.8%) tumors were either diagnosed accurately or as round cell sarcoma, while 3 (1.7%) were reported as suspicious. In one case (0.5%), the material was unsatisfactory. No false negative samples were seen. When FNA morphology was correlated with different histological subtypes, the alveolar subtype RMSs were more cellular than the nonalveolar ones (91.4% vs. 64.9%). Similarly, alveolar subtype RMSs compared with nonalveolar ones exhibited more rhabdomyoblastic cells (77.1% vs. 52.7%), alveolar structures (67.6% vs. 10.8%), giant, multinucleated cells (22.9% vs. 6.7%), mitotic figures (57.1% vs. 18.9%), and cyto-nuclear atypia (77.1% vs. 43.2%). Inversely, spindle-shaped cells were more frequently seen in nonalveolar versus alveolar RMSs (37.8% vs. 20.9%).

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 score0.042
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.028
GPT teacher head0.308
Teacher spread0.280 · 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

Citations70
Published2007
Admission routes1
Has abstractyes

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