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Record W3214498242 · doi:10.1016/s2213-8587(21)00267-9

Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals

2021· article· en· W3214498242 on OpenAlexaff

Bibliographic record

VenueThe Lancet Diabetes & Endocrinology · 2021
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsYork University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesHorizon 2020Abbott Diabetes CareBerlin Institute of HealthRoche Diabetes CareStiftung CharitéNovo Nordisk FondenRegion HovedstadenSanofiEuropean CommissionInternational Society for Pediatric and Adolescent DiabetesNovo NordiskDexcomInsulet CorporationTechnology Agency of the Czech RepublicWellcome TrustSteno Diabetes Center CopenhagenStanford Maternal and Child Health Research InstituteDeutsche ForschungsgemeinschaftEli Lilly and Company
KeywordsStatement (logic)Consensus conferenceInsulin deliveryMEDLINEEvidence-based medicineKey (lock)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.170
metaresearch head score (Gemma)0.205
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.170
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1700.205
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0050.004
Science and technology studies0.0020.004
Scholarly communication0.0090.009
Open science0.0100.011
Research integrity0.0240.024
Insufficient payload (model declined to judge)0.0110.011

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 head0.065
GPT teacher head0.429
Teacher spread0.365 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations111
Published2021
Admission routes1
Has abstractno

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