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Record W4366228181 · doi:10.29327/5203093.1-3

PERFIL EPIDEMIOLÓGICO DE CRIANÇAS ATENDIDAS EM UM PROGRAMA DE VIGILÂNCIA DO DESENVOLVIMENTO INFANTIL E INTERVENÇÃO PRECOCE ENTRE OS ANOS DE 2020 E 2022

2023· book-chapter· pt· W4366228181 on OpenAlexaff
Alessa de França Cunha Medeiros, Daniela Lima Silva, Marta Caroline Araújo da Paixão, Vitória Maria de Souza Leite, Débora Gonçalves da Silva Sarmanho, Maria de Fátima Góes da Costa

Bibliographic record

VenueHawking eBooks · 2023
Typebook-chapter
Languagept
FieldHealth Professions
TopicMaternal and Neonatal Healthcare
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsHumanitiesPsychologyGynecologyMedicinePhilosophy

Abstract

fetched live from OpenAlex

O desenvolvimento infantil (DI) é um conceito amplo que abrange o processo de aquisição de habilidades, de acordo com a idade adequada. Existem fatores que influenciam nesse processo, dentre os quais se pode citar: fatores biológicos, psicossociais e ambientais que afetam o seu decurso, principalmente, no período pré-natal e nos primeiros três anos de vida da criança (CARDOSO et al., 2021).

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.070
GPT teacher head0.381
Teacher spread0.312 · 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 designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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