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Record W3207422029 · doi:10.1002/9781119413936.ch173

Outcomes in Pediatric Orthopedics

2021· other· en· W3207422029 on OpenAlexaff
Unni Narayanan

Bibliographic record

VenueEvidence-Based Orthopedics · 2021
Typeother
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsCerebral palsyOrthopedic surgeryConceptualizationMedicinePhysical therapyPhysical examinationPhysical medicine and rehabilitationMedical physicsIntensive care medicineSurgeryComputer science

Abstract

fetched live from OpenAlex

This chapter presents a case scenario of a 10-year-old boy with bilateral spastic cerebral palsy (CP). It reviews current concepts of outcome measurement, highlighting frameworks for the conceptualization of outcomes, with an emphasis on patient-reported outcomes and the challenges pertinent to measuring these in children. Pediatric orthopedics has a relatively short history of recognizing the importance of measuring outcomes. In the management of ambulatory CP, the technical objective of multilevel surgery is to address the impairments such as muscle contractures and bony deformities. Despite advances in our understanding of outcomes assessment, much of the literature on pediatric orthopedic conditions continues to focus on physical examination findings and radiographic measurements. The chapter provides an overview of the principles of outcomes development and measurement, and a framework to define more meaningfully what “works” for patients. It also provides recommendations for implementing evidence-based practice in the clinical setting.

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)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.045
GPT teacher head0.314
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueEvidence-Based OrthopedicsSame topicCerebral Palsy and Movement DisordersFrench-language works237,207