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Record W2996573152 · doi:10.1590/0034-7167-2017-0899

Accessibility of children with special health needs to the health care network

2019· article· en· W2996573152 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista Brasileira de Enfermagem · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMaternal and Neonatal Healthcare
Canadian institutionsMcGill University
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsReferralNursingThematic analysisHealth careFamily healthSpecial needsQualitative researchDescriptive researchExploratory researchPsychologyMedicinePsychiatrySociology

Abstract

fetched live from OpenAlex

OBJECTIVE: To know how children with special health needs access the health care network. METHOD: This is a qualitative research of descriptive-exploratory type, developed using semi-structured interviews mediated by the Talking Map design. Participants were 19 family caregivers of these children in two Brazilian municipalities. Data were submitted to inductive thematic analysis. RESULTS: Difficulties were mentioned from the diagnosis moment to the specialized follow-up, something represented by the itinerary of the c hild and his/her family in the search for the definition of the medical diagnosis and the access to a specialized professional; a gap between the children's needs and the care offered was observed in primary health care. CONCLUSION: The access of children with special health needs is filled with obstacles such as slowness in the process of defining the child's diagnosis and referral to a specialist. Primary health care services were replaced by care in emergency care units.

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.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.403
Teacher spread0.359 · 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