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Record W2334652692 · doi:10.1097/pcc.0b013e3182211d66

Monitoring in pediatric cardiac critical care: A worldwide perspective

2011· article· en· W2334652692 on OpenAlexaff
Neil Spenceley, Graeme MacLaren, Niranjan Kissoon, Duncan Macrae

Bibliographic record

VenuePediatric Critical Care Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsMedicineCritically illIntensive care medicineGold standard (test)Hypoxia (environmental)Internal medicineOxygen

Abstract

fetched live from OpenAlex

Our ability to directly monitor the mechanisms that govern cellular function, oxygen use, and survival is minimal. Therefore, in critically ill children, surrogate markers are used to try to detect evolving or established hypoxia. These surrogate markers are best used in combination and are complementary to clinical examination. Regardless of resource limitations, we propose that the availability of certain monitoring tools form a standard of care without which pediatric cardiac critical care cannot be safely or optimally provided. These tools include standard invasive hemodynamic monitoring with electrocardiography, lactate measurement, central venous oxygen saturation, and echocardiography. Ultimately, monitoring is only useful when the clinician observes a specific value or trend and has the expertise to act appropriately.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.035
GPT teacher head0.353
Teacher spread0.317 · 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.

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

Citations18
Published2011
Admission routes1
Has abstractyes

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