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Record W3118368829 · doi:10.11575/prism/38502

All Our Families: Five Year Follow-Up (Q7) Descriptive Report March 2020

2020· article· en· W3118368829 on OpenAlexfundno aff
Suzanne Tough, Sheila McDonald, Muci Wu

Bibliographic record

VenueOpen MIND · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
FundersAlberta InnovatesAlberta Children's Hospital FoundationChildren's Hospital Foundation
KeywordsDescriptive researchStatisticsMathematics

Abstract

fetched live from OpenAlex

The All Our Families cohort includes over 3,000 mothers and children who have been participants since the mothers were pregnant. This report is a summary of information collected when the children were 5 years of age. Recruitment into the All Our Families (formerly All Our Babies) cohort began in 2008 and concluded in 2011. Since then, we have collected information twice during pregnancy and at 4 months postpartum, as well as 1 year, 2 years, 3 years and 5 years post-birth. This report presents findings from All Our Families mothers and children at 5 years of age and integrates information from earlier time points. The history of this cohort is described and more details can be found at allourfamiliesstudy.com.

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)0.002
metaresearch head score (Gemma)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.008

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 head0.154
GPT teacher head0.463
Teacher spread0.309 · 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
Published2020
Admission routes1
Has abstractyes

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