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Record W2419325951 · doi:10.1093/pch/21.5.265

An update to the Greig Health Record: Preventive health care visits for children and adolescents aged 6 to 17 years – Technical report

2016· article· en· W2419325951 on OpenAlexaffabout
Anita Arya Greig, Evelyn Constantin, Claire LeBlanc, Bruno Riverin, Patricia Tak-Sam Li, Carl Cummings

Bibliographic record

VenuePaediatrics & Child Health · 2016
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsCanadian Paediatric Society
Fundersnot available
KeywordsChecklistMedicineFamily medicineHealth carePreventive carePsychology

Abstract

fetched live from OpenAlex

The Greig Health Record is an evidence-based health promotion guide for clinicians caring for children and adolescents 6 to 17 years of age. It provides a template for periodic health visits that is easy to use and adaptable for electronic medical records. On the record, the strength of recommendations is indicated in boldface for good, in italics for fair, and in regular typeface for recommendations based on consensus or inconclusive evidence. Checklist templates include sections for Weight, Height and BMI, Psychosocial history and Development, Nutrition, Education and Advice, Specific Concerns, Examination, Assessment, Immunization, and Medications. Included with the checklist tables are five pages of selected guidelines and resources. This update includes information from recent guidelines and research in preventive care for children and adolescents 6 to 17 years of age. Regular updates are planned. The complete Greig Health Record can be found online at the Canadian Paediatric Society's website: www.cps.ca.

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)0.020
metaresearch head score (Gemma)0.106
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: Other · Consensus signal: none
Teacher disagreement score0.188
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.106
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0110.020
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0030.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0450.043

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 head0.016
GPT teacher head0.366
Teacher spread0.350 · 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
GenreOther

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

Citations18
Published2016
Admission routes2
Has abstractyes

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