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Record W4213385514 · doi:10.1016/j.jcte.2022.100295

The multinational onversations and eactions round evere ypoglycemia (CRASH) study: Impact of health care provider communications and recommendations on people with diabetes

2022· article· en· W4213385514 on OpenAlexaff
Frank J. Snoek, Erik Spaepen, Donna Mojdami, Elisabeth Mönnig, Kristen Syring, Yu Yan, Beth Mitchell

Bibliographic record

VenueJournal of Clinical & Translational Endocrinology · 2022
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsEli Lilly (Canada)
FundersDiabetes FondsNovo NordiskSanofiRoche Diabetes CareEli Lilly and Company
KeywordsMedicineMultinational corporationCrashHypoglycemiaHealth careEvent (particle physics)Medical emergencyDiabetes mellitusNursingFamily medicineBusinessEconomic growth

Abstract

fetched live from OpenAlex

The multinational CRASH study found that substantive recommendations from health care providers were predictive of actions taken by people with diabetes during and after a severe hypoglycemic event, which highlights the importance of equipping people with actionable strategies to prevent and treat severe hypoglycemia should a severe hypoglycemic event arise.

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)0.000
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 score0.075
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.072
GPT teacher head0.453
Teacher spread0.381 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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