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Record W2974685430 · doi:10.5489/cuaj.6229

2019 AUQ congrès annuel : Résumés

2019· article· fr· W2974685430 on OpenAlexfundvenueno aff
Editor CUAJ

Bibliographic record

VenueCanadian Urological Association Journal · 2019
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
FundersUniversità degli Studi di BresciaUniversità degli Studi di TorinoUniversitätsklinikum Hamburg-EppendorfMcMaster UniversityMedizinische Universität WienUniversität Wien
KeywordsVirologyMedicine

Abstract

fetched live from OpenAlex

Introduction : Nous avons test l'effet du traitement multimodal, dfini comme cystectomie radicale avec chimiothrapie ou radiothrapie, sur la mortalit due au cancer chez les patients atteints de cancer non-urothlial de la vessie pT2-3 non mtastatique compar l'utilisation de la cystectomie radicale seule. Mthodes : Dans la base de donnes SEER, 887 les patients avec carcinome non-urothlial pT2-3 M0 ont t identifis. Des courbes Kaplan-Meier, des rgressions de Cox uni-et multivaries ont utilis pour les analyses de survie. Rsultats : Le carcinome neuroendocrine (NE) reprsentait 27.7% de notre population, alors que le carcinome pidermode et l'adnocarcinome -56.3% et 16.0%, respectivement. Le traitement multimodal tait plus frquent chez les patients atteints de NE (69.1%). Le taux de mortalit due au cancer 5 ans chez les patients avec NE tait significativement plus faible dans le sous-groupe trait avec approche multimodale versus ceux avec cystectomie radicale seule (37.0 vs 51.5%, p<0.01). Cet avantage n'a pas t observ chez les patients atteints de carcinome pidermode ni chez ceux atteints d'adnocarcinome. Dans les analyses multivaries, le traitement multimodal tait un facteur protecteur chez les patients atteints de NE (ratio des risques 0.58, p = 0.03). Conclusions : Seulement les patients atteints de NE bnficie d'un plus faible taux de mortalit avec l'utilisation du traitement par approche multimodale.

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)0.009
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.669
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0520.034

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 head0.079
GPT teacher head0.399
Teacher spread0.320 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2019
Admission routes2
Has abstractyes

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