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Record W2617706798 · doi:10.3390/children4050041

Respiratory Care Considerations for Children with Medical Complexity

2017· review· en· W2617706798 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

VenueChildren · 2017
Typereview
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsHospital for Sick ChildrenHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
Fundersnot available
KeywordsIntensive care medicineMedicineRespiratory careHealth careRespiratory systemIntensive careRespiratory diseaseHealth technologyLungInternal medicine

Abstract

fetched live from OpenAlex

Children with medical complexity (CMC) are a growing population of diagnostically heterogeneous children characterized by chronic conditions affecting multiple organ systems, the use of medical technology at home as well as intensive healthcare service utilization. Many of these children will experience either a respiratory-related complication and/or they will become established on respiratory technology at home during their care trajectory. Therefore, healthcare providers need to be familiar with the respiratory related complications commonly experienced by CMC as well as the indications, technical and safety considerations and potential complications that may arise when caring for CMC using respiratory technology at home. This review will outline the most common respiratory disease manifestations experienced by CMC, and discuss various respiratory-related treatment options that can be considered, including tracheostomy, invasive and non-invasive ventilation, as well as airway clearance techniques. The caregiver requirements associated with caring for CMC using respiratory technology at home will also be reviewed.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
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 head0.184
GPT teacher head0.406
Teacher spread0.222 · 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