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Record W2005973928 · doi:10.3390/ph5010079

89Zr-Radiolabeled Trastuzumab Imaging in Orthotopic and Metastatic Breast Tumors

2012· article· en· W2005973928 on OpenAlexfundno aff
Albert J. Chang, Ravindra Desilva, Sandeep Jain, Kimberley Lears, Buck E. Rogers, Suzanne E. Lapi

Bibliographic record

VenuePharmaceuticals · 2012
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsnot available
FundersBC Cancer AgencyU.S. Department of Energy
KeywordsTrastuzumabMedicineMetastatic breast cancerOncologyBreast cancerRadiologyPathologyInternal medicineCancer

Abstract

fetched live from OpenAlex

The human epidermal growth factor receptor 2 (HER2/neu) is overexpressed in 20-30% of breast cancers and is associated with tumor growth, angiogenesis, and development of distant metastases. Trastuzumab, an anti-HER2 monoclonal antibody, is used for the treatment of HER2 positive breast cancer and clinical efficacy of this agent is dependent on HER2 expression. Targeted PET imaging of HER2 with radiolabeled trastuzumab may be used to determine HER2 expression levels and guide therapy selection. The purpose of the current study was to evaluate a facile 89Zr-trastuzumab preparation method that can be efficiently applied for clinical grade production. Also, relative HER2 expression levels in orthotopic and metastatic breast cancer models were assessed by PET imaging using the 89Zr-trastuzumab produced by this simpler method.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.384
Teacher spread0.339 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations65
Published2012
Admission routes1
Has abstractyes

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