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Record W3022717627 · doi:10.1002/cncr.32875

Molecular testing for lung adenocarcinoma: Is it time to adopt a “plasma‐first” approach?

2020· editorial· en· W3022717627 on OpenAlexaff
Maisam Makarem, Natasha B. Leighl

Bibliographic record

VenueCancer · 2020
Typeeditorial
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineLungOncologyAdenocarcinomaPrecision medicineLung cancerInternal medicineIntensive care medicinePathologyBioinformaticsCancer researchCancer

Abstract

fetched live from OpenAlex

There is growing evidence that plasma cell‐free DNA testing can aid in the diagnosis of targetable alterations at diagnosis in patients with advanced nonsquamous lung carcinoma. A plasma‐first approach will facilitate access to precision medicine, with studies suggesting that nearly 60% of patients could benefit compared with the current approach of tissue profiling alone.

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 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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations20
Published2020
Admission routes1
Has abstractyes

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