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Record W4386969012 · doi:10.1016/j.acap.2023.09.013

Co-Creation of a Novel Childhood Onset Rare Disease Self-Care Support Tool

2023· article· en· W4386969012 on OpenAlexaboutno aff
Christine Twomey, Enda McGonigle, Ameenat Lola Solebo

Bibliographic record

VenueAcademic Pediatrics · 2023
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsnot available
FundersNIHR Great Ormond Street Hospital Biomedical Research CentreDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsMedicineMental healthQuality of life (healthcare)Mental illnessPopulationPsychiatryChronic conditionDiseaseChronic diseasePediatricsFamily medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

Children with chronic health problems are disproportionately affected by later life mental health disorders.1–3 Treatment regimens, medical monitoring, and life under the ‘shadow of threat’ all contribute to poor mental health outcomes.1,2 The negative impact on well-being is further compounded by the isolation that comes with a diagnosis of a rare disorder.4 Key ameliorators of this negative impact are the engagement and empowerment of children in their own care.3

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)0.011
metaresearch head score (Gemma)0.060
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.060
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0320.011

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 head0.047
GPT teacher head0.426
Teacher spread0.379 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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