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Record W2044227111 · doi:10.1200/jco.2006.10.3051

Vascular Endothelial Growth Factor Levels in Immunodepleted Plasma of Cancer Patients As a Possible Pharmacodynamic Marker for Bevacizumab Activity

2007· letter· en· W2044227111 on OpenAlexaff
Fotios Loupakis, Alfredo Falcone, Gianluca Masi, Anna Fioravanti, Robert S. Kerbel, Mario Del Tacca, Guido Bocci

Bibliographic record

VenueJournal of Clinical Oncology · 2007
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBevacizumabPharmacodynamicsVascular endothelial growth factorCancerSurrogate endpointPharmacologyInternal medicineCancer researchOncologyVEGF receptorsPharmacokineticsChemotherapy

Abstract

fetched live from OpenAlex

United States airport high-tech fingerprint identification equipment was unable to identify her fingerprints. As a result, the very first time she returned to the United States from Spain, she was retained at customs for several hours. The second time, an oncol-ogy clinical report had to be faxed to allow her to enter the United States. To our knowledge, this is the first report of a drug-related fingerprint misidentification.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
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 head0.067
GPT teacher head0.428
Teacher spread0.361 · 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

Citations63
Published2007
Admission routes1
Has abstractyes

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