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Record W3153315604 · doi:10.1002/9781119570097.ch53

Clinical Usefulness of Biological Markers in Pancreatic Cancer

2021· other· en· W3153315604 on OpenAlexaboutno aff
David Anz, Ignazio Piseddu, Marlies Köpke, Ujjwal Mukund Mahajan, Julia Mayerle

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsBiomarkerPancreatic cancerCA19-9CancerPancreatitisBiomarker discoveryMedicineInternal medicineStage (stratigraphy)DiseaseIncidence (geometry)OncologyTumor markerCancer researchBiologyProteomicsGene

Abstract

fetched live from OpenAlex

Pancreatic cancer (PC) represents the fourth leading cause of cancer-related deaths in the United States and Canada and its incidence is increasing in the Western world. So far, the only clinically established biomarker is CA19-9, but it is useful only for disease monitoring. This chapter revises the clinical usefulness of CA19-9 and reviews the latest stage of early tumor detection by novel biomarkers. The only clinically established biomarker for PC so far is the molecule CA19-9, also known as sialylated Lewis an antigen. Once CA19-9 is overexpressed by the tumor and detectable in the serum, it can be used as a follow-up parameter. The largest trial on metabolic biomarkers identified a set of nine metabolites that, together with CA19-9, differentiates between PC and patients with chronic pancreatitis with high sensitivity and specificity.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.153
GPT teacher head0.448
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

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