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Record W3040650012 · doi:10.1038/s41571-020-0392-0

ctDNA applications and integration in colorectal cancer: an NCI Colon and Rectal–Anal Task Forces whitepaper

2020· review· en· W3040650012 on OpenAlexaff
Arvind Dasari, Van K. Morris, Carmen J. Allegra, Chloé E. Atreya, Al B. Benson, Patrick M. Boland, Ki Yong Chung, Mehmet Sitki Copur, Ryan B. Corcoran, Dustin A. Deming, Andrea Dwyer, Maximilian Diehn, Cathy Eng, Thomas J. George, Marc J. Gollub, Rachel Goodwin, Stanley R. Hamilton, Jaclyn F. Hechtman, Howard S. Höchster, Theodore S. Hong, Federico Innocenti, Atif Iqbal, Samuel A. Jacobs, Hagen F. Kennecke, James J. Lee, Christopher H. Lieu, Heinz‐Josef Lenz, O. Wolf Lindwasser, Clara Montagut, Bruno C. Odisio, Fang‐Shu Ou, Laura Porter, Kanwal Raghav, Deborah Schrag, Aaron J. Scott, Qian Shi, John H. Strickler, Alan P. Venook, Rona Yaeger, Greg Yothers, Y. Nancy You, Jason A. Zell, Scott Kopetz

Bibliographic record

VenueNature Reviews Clinical Oncology · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsOttawa Hospital
FundersNational Center for Advancing Translational SciencesNational Cancer Institute
KeywordsMedicineColorectal cancerMultidisciplinary approachTask forceOncologyInternal medicineMinimal residual diseaseDiseaseMEDLINECancerIntensive care medicine

Abstract

fetched live from OpenAlex

An increasing number of studies are describing potential uses of circulating tumour DNA (ctDNA) in the care of patients with colorectal cancer. Owing to this rapidly developing area of research, the Colon and Rectal-Anal Task Forces of the United States National Cancer Institute convened a panel of multidisciplinary experts to summarize current data on the utility of ctDNA in the management of colorectal cancer and to provide guidance in promoting the efficient development and integration of this technology into clinical care. The panel focused on four key areas in which ctDNA has the potential to change clinical practice, including the detection of minimal residual disease, the management of patients with rectal cancer, monitoring responses to therapy, and tracking clonal dynamics in response to targeted therapies and other systemic treatments. The panel also provides general guidelines with relevance for ctDNA-related research efforts, irrespective of indication.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.003

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 head0.049
GPT teacher head0.449
Teacher spread0.400 · 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

Citations365
Published2020
Admission routes1
Has abstractyes

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