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Record W2064641168 · doi:10.3810/pgm.2014.05.2760

Biosimilar Insulins Are Coming: The Top 10 Things you Should Know

2014· review· en· W2064641168 on OpenAlexaff
Ian Blumer, Steven V. Edelman

Bibliographic record

VenuePostgraduate Medicine · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsDiabetes Canada
FundersSanofiCilagGlaxoSmithKlineAstraZeneca
KeywordsBiosimilarMedicineDrugIntensive care medicineInternet privacyRisk analysis (engineering)PharmacologyInternal medicineComputer science

Abstract

fetched live from OpenAlex

Biologic drugs, such as currently prescribed insulins, are large, complex, 3-dimensional molecules manufactured in biological systems. The complexity of the structure of the biologic drug and its manufacturing process means that it is challenging to create a biologic drug that is identical to the original branded drug. With the potential availability on the horizon of follow-on insulin products (also known as biosimilar insulins) in the United States and other countries where they are not currently in use, physicians (and other prescribers) need to be aware of the potential benefits and concerns regarding biosimilar insulins in order to facilitate informed decision making and to provide the best possible advice and guidance to their patients with diabetes. This article offers a brief, practical overview regarding biosimilar insulins by answering 10 key questions about the topic.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.856
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.122
GPT teacher head0.384
Teacher spread0.262 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2014
Admission routes1
Has abstractyes

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