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Record W2904882484 · doi:10.1093/jncics/pky061

Population Frequency of Serous Tubal Intraepithelial Carcinoma (STIC) in Clinical Practice Using SEE-Fim Protocol

2018· article· en· W2904882484 on OpenAlex

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

VenueJNCI Cancer Spectrum · 2018
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSerous carcinomaMedicineSalpingectomySerous fluidGynecologyPopulationFallopian tubeMedical diagnosisOvarian cancerObstetricsPathologyCancerInternal medicinePregnancy

Abstract

fetched live from OpenAlex

2 mutation carriers undergoing risk-reducing surgery prompted the hypothesis that many adnexal high-grade serous carcinomas (HGSCs) arise from the fallopian tube, rather than the ovary, as supposed. The changing paradigm has important implications for HGSC prevention. Most data related to the frequency of STIC are derived from case series and estimates vary widely. Therefore, we analyzed population-based data from 10 523 surgeries including salpingectomy (Jan 2014-Dec 2016) that were examined using the "Sectioning and Extensively Examining the Fimbria" protocol, which optimizes STIC detection. Overall, STIC was detected in 40 (0.38%) specimens, including 32 diagnosed with concurrent gynecologic cancer. STIC was detected in 8 (<0.01%) of 9392 cases with benign diagnoses. We conclude that the relative rarity of STIC diagnoses in routine pathology practice has critical implications for research aiming to elucidate the pathogenesis of HGSC and developing prevention strategies.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.022
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

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

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 head0.052
GPT teacher head0.425
Teacher spread0.373 · 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