MétaCan
Menu
Back to cohort
Record W2511342761 · doi:10.21037/atm.2016.08.19

Skin communicates what we deeply feel: antibiotic prophylactic treatment to reduce epidermal growth factor receptor inhibitors induced rash in lung cancer (the Pan Canadian rash trial)

2016· letter· en· W2511342761 on OpenAlexaboutno aff
Óscar Arrieta, Maria Teresa de Jesus Vega, Mariana López-Mejía, Andrés F. Cardona

Bibliographic record

VenueAnnals of Translational Medicine · 2016
Typeletter
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEpidermal growth factor receptorRashMedicineGefitinibLung cancerEGFR inhibitorsAdverse effectChemotherapyAdenocarcinomaErlotinibCancerDermatologyCancer researchInternal medicineOncology

Abstract

fetched live from OpenAlex

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) represent a major breakthrough for patients with metastatic lung adenocarcinoma primarily exhibiting an EGFR -activating oncogenic mutation. The ability of EGFR inhibitors to block specific molecular pathways driving uncontrolled cellular division in cancer has resulted in a decreased incidence of serious systemic adverse events commonly associated with conventional cytotoxic chemotherapy. However, due to the abundant expression of EGFR in the skin and adnexal structures, cutaneous adverse events (CAEs) to EGFR inhibitors are frequent (1).

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.093
GPT teacher head0.368
Teacher spread0.275 · 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
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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of Translational MedicineSame topicColorectal Cancer Treatments and StudiesFrench-language works237,207