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Record W4312185378 · doi:10.7759/cureus.32839

A Single-Center Study of Patients With Synchronous Primary Malignancy: A Case Series

2022· article· en· W4312185378 on OpenAlexaff
Abeer I Alsulaimani, Layla M Alkhaldi, Sheikha A AlTawairqi, Arif Khurshid, Hamma A Abdulaziz, Abdulrahman G Alotaibi, Haifa O Alotaibi

Bibliographic record

VenueCureus · 2022
Typearticle
Languageen
FieldMedicine
TopicMultiple and Secondary Primary Cancers
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineMalignancyIncidence (geometry)RectumSeries (stratigraphy)KidneyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Multiple primary malignant tumors (MPMT) can be defined as more than two different tumors synchronously or metachronously forming in the same organ or different organs. The incidence of MPMTs varies dramatically between antemortem and postmortem examinations, becoming a serious medical issue. Evidence shows that the overall incidence of MPMTs is between 2.4% and 17%. Double primary malignancy (DPM) is considered the most common type of MPMT. In this case series, we present three cases of MPMT. The first case involved the colon and the breast, the second case involved the colon and the kidney, and the third case involved rectum and kidney.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.227
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations3
Published2022
Admission routes1
Has abstractyes

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