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Record W2572698146 · doi:10.4251/wjgo.v9.i1.42

Pre-treatment platelet counts as a prognostic and predictive factor in stage II and III rectal adenocarcinoma

2017· article· en· W2572698146 on OpenAlexaff
Morgan Steele, Ioannis A. Voutsadakis

Bibliographic record

VenueWorld Journal of Gastrointestinal Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsNOSM UniversitySault Area Hospital
Fundersnot available
KeywordsMedicineCarcinoembryonic antigenInternal medicinePlateletGastroenterologyLog-rank testStage (stratigraphy)AdenocarcinomaColorectal cancerAdjuvantRetrospective cohort studyAdjuvant therapyComplete responseSurvival analysisSurgeryCancerChemotherapy

Abstract

fetched live from OpenAlex

AIMTo investigate if pre-treatment platelet counts could provide prognostic information in patients with rectal adenocarcinoma that received neo-adjuvant treatment. METHODSPlatelet number on diagnosis of stage II and III rectal cancer was evaluated in 51 patients receiving neoadjuvant treatment and for whom there were complete follow-up data on progression and survival, as well as pathologic outcome at the time of surgery.Pathologic responses on the surgical specimen of patients with lower platelet counts (150-300 × 10 9 /L) were compared with these of patients with higher platelet counts (> 300 × 10 9 /L) by the χ 2 test.Overall and progression free survival Kaplan-Meier curves of the two groups were constructed and compared with the Log-Rank test. RESULTSA significant difference was present between the two groups in regards to pathologic response with patients with lower platelet counts being more likely to exhibit a Retrospective

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.313
Teacher spread0.292 · 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 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

Citations16
Published2017
Admission routes1
Has abstractyes

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Same venueWorld Journal of Gastrointestinal OncologySame topicInflammatory Biomarkers in Disease PrognosisFrench-language works237,207