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Record W3017629659 · doi:10.1177/0883073820918454

Contextualized Autonomy in Transitional Care for Youth With Neurologic Conditions: The Role of the Pediatric Neurologist

2020· article· en· W3017629659 on OpenAlexaff
Aline Bogossian, Annette Majnemer, Éric Racine

Bibliographic record

VenueJournal of Child Neurology · 2020
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsMontreal Clinical Research InstituteMcGill UniversityMontreal Children's HospitalCentre for Interdisciplinary Research in RehabilitationMcGill University Health CentreUniversité de Montréal
Fundersnot available
KeywordsAutonomyContext (archaeology)Pediatric NeurologyTransition (genetics)Adult carePsychologyHealth careSocial workTransitional careDevelopmental psychologyMedicinePediatricsYoung adultPolitical science

Abstract

fetched live from OpenAlex

Youth with neurologic conditions experience multiple life transitions. The transfer from pediatric to adult health care systems exemplifies one such complex and multifaceted transition that occurs in parallel with developmental, legal, and social changes that may influence the roles and responsibilities of youth and their caregivers. As a result, ethical situations, questions, and challenges may surface in transition care to which pediatric neurologists may be confronted. In this article, we focus on the topic of autonomy and situations that may arise in transition care in the context of pediatric neurology. Building from a clinical case, we present the concept of contextualized autonomy to work through the questions that arise in the case and propose ways of thinking through those challenging situations in transition care.

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)0.007
metaresearch head score (Gemma)0.012
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 score0.012
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.018
Scholarly communication0.0060.006
Open science0.0020.014
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.336
Teacher spread0.296 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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