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Record W1514246966 · doi:10.1186/cc2806

Signal merging and signal fusion to enhance robustness and reduce false alarms during multichannel patient monitoring

2004· article· en· W1514246966 on OpenAlexaff
E. Braithwaite, James H. Price, Lionel Tarassenko, Duncan Young, William J. Sibbald

Bibliographic record

VenueCritical Care · 2004
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsSunnybrook Hospital
FundersB. Braun MelsungenEli Lilly and Company
KeywordsMedicineVital signsRespiratory rateHeart rateOxygen saturationPhotoplethysmogramHabituationEarly warning scoreWarning systemEmergency medicineIntensive care medicineMedical emergencyBlood pressureAnesthesiaComputer scienceInternal medicineAudiology

Abstract

fetched live from OpenAlex

on Intensive Care and Emergency Medicine seal is maintained by gentle pressure on the TT keeping the cuff pressing on the vocal cords.During percutaneous tracheostomy the bougie remains in the trachea.When ventilation through the tracheostomy tube (cuff inflated) is confirmed, the TT and bougie are withdrawn.Throughout the procedure, if ventilation difficulties occur, the TT can be easily re-inserted using the bougie as a guide.Results Three different bougies were used: types (number used) were Eschmann (29), size 10 Portex disposable (four) and size 12 Portex disposable (13).Three patients were trauma cases: a neutral cervical position was maintained.In 33 cases the Blue Rhino dilator and in 12 cases the Ultra-Perc (White Rhino) dilator was used.One case was a serial dilator (see later). ConclusionThe bougie for airway control for percutaneous tracheostomy was associated with zero hypoxic episodes in 46 cases.Minor bougie damage in two cases caused no problems.Other complications seen were either minor or unlikely to be due to the bougie. P3Percutaneous dilational tracheostomy in critically ill patients: progressive vs single dilatation techniques

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.348
Teacher spread0.322 · 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 designBench or experimental
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

Citations0
Published2004
Admission routes1
Has abstractyes

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