MétaCan
Menu
Back to cohort

Mutagenesis Associated with DNA-Damage-Stress Response

2016· article· en· W2334177902 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Analytical Oncology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsOverdiagnosisMedicineHarmDiseaseIntensive care medicineCancerStage (stratigraphy)Clinical trialInternal medicineOncologyPsychologyBiology

Abstract

fetched live from OpenAlex

In this manuscript we aim to take on the controversies in oncology, such as those related to costs and screening guidelines. Are we recently at new turning point with our existing methodology? During the past 30 years of evolution methods of awareness and screening have lead to an emphasis on early diagnoses of cancer and not only cancer. Recent trends and clinical trials show that these goals have not been met. International data demonstrate significant increase in early stage disease, without a proportional decrease in later-stage disease. We need to more differentiate in methodology because cancers are heterogenous with multiple paths, not all of which progress to metastases and death. This broader definition of disease named cancer must include also indolent disease that causes no harm during patients lifetime. Overdiagnosis and overtreatment result in billions of USD of wasted money. Our methodology must be completed with methods which take proper account of the real-life environment.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.281
Teacher spread0.269 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations2
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Analytical OncologySame topicCancer Genomics and DiagnosticsFrench-language works237,207