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Record W1977054881 · doi:10.1097/pep.0000000000000048

Adapting to Higher Demands

2014· article· en· W1977054881 on OpenAlexaff
Dominique Surprenant, Sarah Milne, Katherine Moreau, Nicole D. Robert

Bibliographic record

VenuePediatric Physical Therapy · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsReferralMedicinePatient satisfactionService delivery frameworkPhysical therapyIntervention (counseling)TorticollisService (business)PopulationNursingPsychology

Abstract

fetched live from OpenAlex

PURPOSE: Referrals for torticollis/plagiocephaly have increased dramatically because of "Back to Sleep" campaigns and front-line staff becoming more proficient at recognition and referral to physiotherapy. These infants generally respond well to early intervention so longer waitlists raise concern about clinical outcomes due to delay. METHODS: Therapists developed a group-based, team service delivery model based on best practices in individual treatment programs. The program was implemented and evaluated for assessment and treatment of infants presenting with these conditions, including caregiver satisfaction. RESULTS: Compared with individual treatment, the group format enabled therapists to increase capacity to serve this population by 70%, with equivalent quality and achievement of discharge criteria, as well as a modest service cost saving per child. Caregiver questionnaires indicate satisfaction with the service. CONCLUSIONS: Group service delivery is a cost-effective and efficient way to manage increased referrals for torticollis/plagiocephaly while maintaining comparable treatment outcomes. VIDEO ABSTRACT: For more insights from the authors, see Supplemental Digital Content 1, available at http://links.lww.com/PPT/A64.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.371

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 head0.011
GPT teacher head0.266
Teacher spread0.255 · 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 designNot applicable
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

Citations14
Published2014
Admission routes1
Has abstractyes

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