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Record W1947264119 · doi:10.1586/14737159.2015.1091311

Improving pancreatic cancer diagnosis using circulating tumor cells: prospects for staging and single-cell analysis

2015· review· en· W1947264119 on OpenAlex
Colin M. Court, Jacob S. Ankeny, Shuang Hou, Hsian‐Rong Tseng, James S. Tomlinson

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

VenueExpert Review of Molecular Diagnostics · 2015
Typereview
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsPancreas Centre (Canada)
FundersNational Cancer Institute
KeywordsCirculating tumor cellPancreatic cancerMedicineCancerOncologyInternal medicineCancer researchPathologyMetastasis

Abstract

fetched live from OpenAlex

Pancreatic cancer (PC) is the fourth most common cause of cancer-related death in the USA, primarily due to late presentation coupled with an aggressive biology. The lack of adequate biomarkers for diagnosis and staging confound clinical decision-making and delay potentially effective therapies. Circulating tumor cells (CTCs) are a promising new biomarker in PC. Preliminary studies have demonstrated their potential clinical utility, and newer CTC isolation platforms have the potential to provide clinicians access to tumor tissue in a reliable, real-time manner. Such a 'liquid biopsy' has been demonstrated in several cancers, and small studies have demonstrated its potential applications in PC. This article reviews the available literature on CTCs as a biomarker in PC and presents the latest innovations in CTC research as well as their potential applications in PC.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.671
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.060
GPT teacher head0.374
Teacher spread0.314 · 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