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Record W2119868719 · doi:10.1109/cbms.1991.128945

Database design of an intensive care unit patient data management system

2002· article· en· W2119868719 on OpenAlexafffundabout
N. Fumai, Christine Collet, M. Petroni, K. Roger, Austin Lam, E. Saab, A.S. Malowany, Franco A. Carnevale, Ronald Gottesman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsComputer scienceRelational databaseDatabase designDatabaseData managementDatabase theoryData modelingNetwork managementNetwork monitoringInformation retrievalData miningComputer network

Abstract

fetched live from OpenAlex

A patient data management system (PDMS) developed for use in the intensive care unit (ICU) of the Montreal Children's Hospital is described. The PDMS acquires real-time patient data from a network of physiological bedside monitors, and facilitates the review and interpretation of this data by presenting it as graphical trends, charts, and plots on a color video display. The data management structure integrates varied data types and provides database support for different applications, while preserving the real-time acquisition of network data. This structure is based primarily on OS/2 Extended Edition relational database. The relational database design is expected to solve the query shortcomings of the previous data management structure, as well as offer support for security and concurrency.>

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 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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.228
GPT teacher head0.353
Teacher spread0.126 · 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 designSimulation or modeling
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

Citations5
Published2002
Admission routes3
Has abstractyes

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