MétaCan
Menu
← Back to cohort
Record W2593452645 · doi:10.1503/cmaj.161093

Enhancing implementation research within Canada’s investments in the health of women and children globally

2017· article· en· W2593452645 on OpenAlexafffundvenueabout
Renee Sharma, Helen Scott, Zulfiqar A Bhutta

Bibliographic record

VenueCanadian Medical Association Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsCentre for Global Health ResearchHospital for Sick Children
FundersHospital for Sick Children
KeywordsCornerstoneMillennium Development GoalsPsychological interventionChild survivalChild healthDeveloping countryGlobal healthEconomic growthChild mortalityMedicineEnvironmental healthPediatricsPolitical sciencePublic healthNursingGeography

Abstract

fetched live from OpenAlex

Few issues have received as much global attention in recent years as maternal, newborn and child health and survival, a cornerstone of the United Nations’ Millennium Development Goals. Recent research has focused on defining and developing a range of evidence-based interventions across the

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)0.120
metaresearch head score (Gemma)0.122
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.880
Threshold uncertainty score0.915

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1200.122
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.005
Science and technology studies0.0120.009
Scholarly communication0.0140.005
Open science0.0050.011
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0100.001

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 head0.018
GPT teacher head0.357
Teacher spread0.339 · 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 designTheoretical or conceptual
DomainMethods
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

Citations3
Published2017
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Medical Association Journal→Same topicGlobal Maternal and Child Health→French-language works237,207→