MétaCan
Menu
Back to cohort
Record W3027639216 · doi:10.1139/apnm-2020-0073

Starting strong: Dietary, behavioral, and environmental factors that promote “strength” from conception to age 2 years

2020· review· en· W3027639216 on OpenAlexvenueno aff
Robert Murray

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2020
Typereview
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsSocioemotional selectivity theoryNoveltyDevelopmental psychologyPsychologySummitEpigeneticsBiologySocial psychology

Abstract

fetched live from OpenAlex

Beginning with conception and continuing through childhood and adolescence, the word “strength” connotes the totality of optimal early bone and tissue growth; neural wiring of the brain; and acquisition of fine motor, gross motor, language, and socioemotional skills. The robustness of each of these attributes depend on 3 critical epigenetic (external) factors: the quality of nutrition; positive adult nurturing; and experiences acquired within a stimulating, safe environment that affords free exploration. This review highlights the relationship between the epigenetic factors in the period of conception to age 2 years and a child’s future health, cognitive capacity, and social aptitude, which collectively comprise their “strength”. This paper was presented as part of the 2018 Strength Summit conference entitled, The Role of Strength in Optimal Health and Well-being. Novelty Strength in infants signifies the totality of optimal early growth and neural wiring of the brain. Strength at this life stage also includes the acquisition of motor, language, and socioemotional skills. Three epigenetic factors are critical during birth to 24 months: nutrition, nurturing, and free exploration.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.301
Teacher spread0.252 · 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
GenreReview

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

Citations5
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueApplied Physiology Nutrition and MetabolismSame topicInfant Development and Preterm CareFrench-language works237,207