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Record W4392246465 · doi:10.1016/j.esmoop.2024.102273

44O Updated results from a phase I study evaluating the KRAS G12C inhibitor MK-1084 in solid tumors and in combination with pembrolizumab in NSCLC

2024· article· en· W4392246465 on OpenAlexaff
C.I. Rojas, Iwona Ługowska, Rosalyn A. Juergens, Adrian G. Sacher, Susanne Weindler, Mehmet Alı Nahıt Şendur, Rafał Dziadziuszko, Abhijit Pal, Eduardo Castañón Álvarez, E.S. Ahern, Nehal J. Lakhani, Li‐Chia Chen, Thomas Jemielita, Song‐Yi Choi, Anastasios Stathis

Bibliographic record

VenueESMO Open · 2024
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of TorontoMcMaster University
Fundersnot available
KeywordsKRASPembrolizumabMedicineCancer researchInternal medicineOncologyCancerColorectal cancerImmunotherapy

Abstract

fetched live from OpenAlex

We present updated results from a phase 1 dose-escalation study (NCT05067283) of selective KRAS G12C inhibitor MK-1084 as monotherapy in advanced solid tumors and in combination with pembrolizumab (pembro) for first-line metastatic NSCLC.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.048
GPT teacher head0.402
Teacher spread0.354 · 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 designNon-randomized trial
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

Citations13
Published2024
Admission routes1
Has abstractyes

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