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Record W2405504715 · doi:10.3233/978-1-60750-806-9-115

Next Generation Neonatal Health Informatics with Artemis

2011· article· en· W2405504715 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStudies in health technology and informatics · 2011
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsUniversity of TorontoOntario Tech University
Fundersnot available
KeywordsSoftware deploymentCloud computingComputer scienceHealth informaticsIntensive careInformaticsFidelityHealth careData scienceSoftware engineeringMedicineIntensive care medicineEngineeringTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

This paper describes the deployment of a platform to enable processing of currently uncharted high frequency, high fidelity, synchronous data from medical devices. Such a platform would support the next generation of informatics solutions for neonatal intensive care. We present Artemis, a platform for real-time enactment of clinical knowledge as it relates to multidimensional data analysis and clinical research. Through specific deployment examples at two different neonatal intensive care units, we demonstrate that Artemis supports: 1) instantiation of clinical rules; 2) multidimensional analysis; 3) distribution of services for critical care via cloud computing; and 4) accomplishing 1 through 3 using current technology without a negative impact on patient care.

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.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.182
GPT teacher head0.377
Teacher spread0.194 · 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