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Record W1860559471 · doi:10.1109/acc.1995.529358

Clinical evaluation of long range adaptive control for mean arterial blood pressure regulation

2005· article· en· W1860559471 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSetpointModel predictive controlControl theory (sociology)Mean arterial pressureBlood pressurePressure controlControl systemAdaptive controlComputer scienceHorizonMathematicsControl (management)EngineeringMedicineArtificial intelligenceInternal medicineHeart rate

Abstract

fetched live from OpenAlex

A computerized drug delivery system has been designed for automatic regulation of mean arterial pressure (MAP) of human patients by infusion of a vasodilator (sodium nitroprusside). This control system employs a predictive control algorithm with a combination of finite-horizon and an infinite horizon optimization terms. The control algorithm operates in an adaptive mode by coupling it to a recursive, control-relevant identification algorithm for long-range predictive control. The proposed system was used to perform closed-loop regulation of MAP of two patients, in an intra-operative environment, in the cardiac unit of the University of Alberta Hospital. The MAP trajectories show that the patient's MAP stayed within /spl plusmn/10 mmHg of the setpoint for more than 70% of the time even in the presence of significant natural disturbances.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.421

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.291
Teacher spread0.265 · 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

Quick stats

Citations12
Published2005
Admission routes2
Has abstractyes

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