MétaCan
Menu
Back to cohort
Record W2080893531 · doi:10.1155/2012/597497

Molecular Events in Primary and Metastatic Colorectal Carcinoma: A Review

2012· review· en· W2080893531 on OpenAlexaffabout
Rani Kanthan, Jenna‐Lynn Senger, Selliah Kanthan

Bibliographic record

VenuePathology Research International · 2012
Typereview
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsMicrosatellite instabilityEpigeneticsColorectal cancerMalignancyChromosome instabilityCarcinogenesisCancer researchGenome instabilityPhenotypeBiologyCancerDiseaseMedicineComparative genomic hybridizationmicroRNABioinformaticsPathologyGeneGeneticsGenomeMicrosatellite

Abstract

fetched live from OpenAlex

Colorectal cancer (CRC) is a heterogeneous disease, developing through a multipathway sequence of events guided by clonal selections. Pathways included in the development of CRC may be broadly categorized into (a) genomic instability, including chromosomal instability (CIN), microsatellite instability (MSI), and CpG island methylator phenotype (CIMP), (b) genomic mutations including suppression of tumour suppressor genes and activation of tumour oncogenes, (c) microRNA, and (d) epigenetic changes. As cancer becomes more advanced, invasion and metastases are facilitated through the epithelial-mesenchymal transition (EMT), with additional genetic alterations. Despite ongoing identification of genetic and epigenetic markers and the understanding of alternative pathways involved in the development and progression of this disease, CRC remains the second highest cause of malignancy-related mortality in Canada. The molecular events that underlie the tumorigenesis of primary and metastatic colorectal carcinoma are detailed in this manuscript.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.163
GPT teacher head0.468
Teacher spread0.305 · 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
GenreReview

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

Citations97
Published2012
Admission routes2
Has abstractyes

Explore more

Same venuePathology Research InternationalSame topicGenetic factors in colorectal cancerFrench-language works237,207