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Record W2039010462 · doi:10.12927/hcq.2011.22581

Kids in Transition: The Rehab Experience

2011· article· en· W2039010462 on OpenAlexaffabout
Cindy Bruce-Barrett, Alastair Hodinott, Arbelle Manicat-Emo, Tonya Flaming, Daune MacGregor, Iris Hogan, Chris Carew, Sandi Cox

Bibliographic record

VenueHealthcare Quarterly · 2011
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsRehabilitationReferralGeneral partnershipNursingChristian ministryMedicineHealth careAcute careRehabilitation hospitalPopulationFamily medicinePhysical therapyPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

Holland Bloorview Kids Rehabilitation Hospital (formerly Bloorview Kids Rehab) is Canada's largest teaching hospital for pediatric rehabilitation and the only in-patient pediatric rehabilitation centre in Ontario. SickKids is a quaternary-level academic health sciences centre. The acute care neuroscience and trauma patient population at SickKids represents the largest volume of transitioning clients between the two organizations. For years, the number of medically unnecessary days associated with patients awaiting transfer from SickKids to Holland Bloorview for off-site rehabilitation was consistently driven by inefficient processes, multiple handovers, duplicitous efforts, fragmented communication and a lack of timely or complete referral information. Recognizing this situation as a threat to access, as well as a significant risk to patient health outcomes, SickKids and Holland Bloorview embarked on an exciting partnership (Kids in Transition: The Rehab Experience) as part of a larger Ministry of Health and Long-Term Care-funded initiative, the Flo Collaborative.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.003
Scholarly communication0.0030.002
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.001

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 head0.118
GPT teacher head0.416
Teacher spread0.297 · 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 designQualitative
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

Citations3
Published2011
Admission routes2
Has abstractyes

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