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Record W2138265569 · doi:10.3899/jrheum.141364

Informational Continuity Is Integral for Successful Transition of Adolescents to Adult Care

2015· letter· en· W2138265569 on OpenAlexvenueno aff
Neil Chanchlani, Marie McGee, J. E. R. McDonagh

Bibliographic record

VenueThe Journal of Rheumatology · 2015
Typeletter
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineContinuity of careTransition (genetics)Transitional careRheumatologyFamily medicineCore (optical fiber)Adult careHealth careQuality (philosophy)Element (criminal law)GerontologyPediatricsYoung adultInternal medicinePolitical science

Abstract

fetched live from OpenAlex

To the Editor: Recent reports have suggested that in spite of rheumatology-specific research in the area, there remained a need for further research and development of transitional care for adolescents reaching adulthood, as highlighted in an editorial and paper in this journal1,2. In the United States, “Six Core Elements of Health Care Transition” have been defined by the federally funded national resource center on transition (Got Transition)3. McManus, et al recently reported a study that observed improvements in all 6 transition quality indicators when these elements were addressed in the clinical setting4. Informational continuity is 1 of several continuities recognized as important in transitional care5 and is reflected in several of the core elements referred to above3,4. Although a medical summary3 as described in core element No. 4 was ranked in the top 2 aspects of successful transition by adult physicians6, … Address correspondence to Dr. N. Chanchlani, Department of Rheumatology, Birmingham Children’s Hospital, Birmingham B4 6NH, UK. E-mail: nchanchlani{at}doctors.org.uk

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)0.003
metaresearch head score (Gemma)0.027
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.018
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0180.021
Insufficient payload (model declined to judge)0.0060.003

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 head0.042
GPT teacher head0.385
Teacher spread0.343 · 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
GenreCommentary

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

Citations10
Published2015
Admission routes1
Has abstractyes

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Same venueThe Journal of RheumatologySame topicAdolescent and Pediatric HealthcareFrench-language works237,207