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Record W2274066308 · doi:10.1586/14737159.2016.1146593

Toward clinical genomics in everyday medicine: perspectives and recommendations

2016· article· en· W2274066308 on OpenAlex
Susan Delaney, Michael Hultner, Howard J. Jacob, David H. Ledbetter, Jeanette McCarthy, M.A. Ball, Kenneth B. Beckman, John W. Belmont, Cinnamon S. Bloss, Michael F. Christman, Andy Cosgrove, Stephen A. Damiani, Timothy Danis, Massimo Delledonne, Michael J. Dougherty, Joel T. Dudley, W. Andrew Faucett, Jennifer Friedman, David H. Haase, T S Hays, Stu Heilsberg, Jeff Huber, Leah Kaminsky, Nikki Ledbetter, Warren H. Lee, Elissa Levin, Ondrej Libiger, Michael D. Linderman, Richard L. Love, David Magnus, AnneMarie Martland, Susan L. McClure, Scott E. Megill, Helen Messier, Robert L. Nussbaum, Latha Palaniappan, Bradley Patay, Bradley W. Popovich, John Quackenbush, Mark J. Savant, Michael M. Su, Sharon F. Terry, Steven Tucker, William T. Wong, Robert C. Green

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 · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsGenome British Columbia
FundersNational Institute of General Medical SciencesNational Human Genome Research InstituteEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Cancer InstituteNational Heart, Lung, and Blood Institute
KeywordsPersonalized medicineViewpointsPrecision medicineExome sequencingGenomicsExomeHealth careMedicineGenomeBioinformaticsBiologyPolitical scienceGeneticsPathology

Abstract

fetched live from OpenAlex

Precision or personalized medicine through clinical genome and exome sequencing has been described by some as a revolution that could transform healthcare delivery, yet it is currently used in only a small fraction of patients, principally for the diagnosis of suspected Mendelian conditions and for targeting cancer treatments. Given the burden of illness in our society, it is of interest to ask how clinical genome and exome sequencing can be constructively integrated more broadly into the routine practice of medicine for the betterment of public health. In November 2014, 46 experts from academia, industry, policy and patient advocacy gathered in a conference sponsored by Illumina, Inc. to discuss this question, share viewpoints and propose recommendations. This perspective summarizes that work and identifies some of the obstacles and opportunities that must be considered in translating advances in genomics more widely into the practice of medicine.

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)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.642
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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 integrity0.0000.000
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 head0.022
GPT teacher head0.354
Teacher spread0.331 · 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