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Record W4401512100 · doi:10.24095/hpcdp.44.7/8.07

Release notice: Perinatal Health Indicators (PHI) Data Tool

2024· article· en· W4401512100 on OpenAlexaffvenueabout
Stephanie Metcalfe, Jennifer Lye, Hongbo Liang, Holly Arscott, Chantal Nelson, Wei Luo

Bibliographic record

VenueHealth Promotion and Chronic Disease Prevention in Canada · 2024
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsNoticeHealth indicatorHealth statisticsInfant mortalityPublic healthHealth informationAgency (philosophy)Environmental healthCommunity healthMedicineHealth careNursingPolitical sciencePopulationSociology

Abstract

fetched live from OpenAlex

The Maternal and Infant Health Section of the Public Health Agency of Canada (PHAC) is pleased to announce an update to the Perinatal Health Indicators (PHI) Data Tool. The interactive Data Tool on the PHAC Infobase website presents statistics on maternal, fetal and infant health in Canada based on data from the Canadian Institute for Health Information's (CIHI) Discharge Abstract Database (DAD), the Canadian Community Health Survey (CCHS), and the Canadian Vital Statistics (birth, stillbirth and death databases). The data include 20 indicators grouped into four key health domains: health behaviours and practices, health services, maternal outcomes, and infant outcomes. For this update, five new indicators were added and three existing ones were modified. To access the latest Perinatal Health Indicators Data Tool, visit https://health-infobase.canada.ca/phi/.

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)0.011
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.304
Threshold uncertainty score0.993

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.073
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.018
Science and technology studies0.0030.001
Scholarly communication0.0070.004
Open science0.0040.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3040.178

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 head0.037
GPT teacher head0.374
Teacher spread0.337 · 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.

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

Citations0
Published2024
Admission routes3
Has abstractyes

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