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Record W3046818137 · doi:10.1177/1078155220945374

Off-label infusion of biosimilar bevacizumab: A provincial experience

2020· article· en· W3046818137 on OpenAlexaff
Marc Geirnaert, Jacy Howarth, Curtis Kellett, Kristen Martin, Scott Streilein, Chad Ricard, Danica Wasney, Saroj Niraula

Bibliographic record

VenueJournal of Oncology Pharmacy Practice · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsBevacizumabBiosimilarMedicinePharmacologySurgeryInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

The product monograph for reference bevacizumab (Avastin) and biosimilar bevacizumab (Mvasi) recommend to infuse the first dose of bevacizumab over 90 min, second dose over 60 min and third and subsequent doses over 30 min. Despite the product monograph recommendations, many institutions adopted an accelerated bevacizumab (Avastin) 0.5 mg/kg/min infusion time. Our province adopted the accelerated infusion time at time of biosimilar bevacizumab (Mvasi) adoption. Our experience with the accelerated infusion time was well tolerated in the first five months of biosimilar bevacizumab adoption across different tumor types.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.092
GPT teacher head0.424
Teacher spread0.332 · 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 designBench or experimental
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

Citations0
Published2020
Admission routes1
Has abstractyes

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