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Record W2769149237 · doi:10.1016/s0140-6736(17)32417-0

Investment in child and adolescent health and development: key messages from Disease Control Priorities , 3rd Edition

2017· review· en· W2769149237 on OpenAlexaff
Donald A. P. Bundy, Nilanthi de Silva, Susan Horton, George Patton, Linda Schultz, Dean T. Jamison, Amina Abubakara, Amrita Ahuja, Harold Alderman, Nicolas Allen, Laura J. Appleby, Elisabetta Aurino, Peter Azzopardi, Sarah Baird, Louise Banham, Jere R. Behrman, Habib Benzian, Sonia Bhalotra, Zulfiqar A Bhutta, Maureen M. Black, Paul Bloem, Chris Bonell, Mark Bradley, Sally Brinkman, Simon Brooker, Carmen Burbano, Nicolas Burnett, Tania Cernuschi, Siân E. Clarke, Carolyn Coffey, Peter Colenso, Kevin Croke, Amy M. Daniels, Elia De la Cruz, Damien de Walque, Anil Deolaikar, Lesley Drake, Lia C. H. Fernald, Meena Fernandes, Deepika Fernando, Günther Fink, Rae Galloway, Aulo Gelli, Andreas Georgiadis, Caroline W. Gitonga, Boitshepo Giyosa, Paul Glewwe, Joseph G. Nzovu, Amber Gove, Natasha Graham, Brian Greenwood, Elena L. Grigorenko, Cai Heath, Joan Hicks, Mélissa Hidrobo, Kenneth Hill, Tara Hill, T. Déirdre Hollingsworth, Elissa Kennedy, Imran Khan, Josephine Kiamba, Jane Kim, Michael Kremer, D. Scott LaMontagne, Zohra S Lassi, Ramanan Laxminarayan, Jacqueline Mahon, Mai Lu, Sebastián Martínez, Sergio Meresman, Edward Miguel, Arlene Mitchell, Sophie Mitra, Anoosh Moin, Ali H. Mokdad, Daniel Mont, Arindam Nandi, Joaniter I. Nankabirwa, Daniel Plaut, Elina Pradhan, Rachel L. Pullan, Nicola Reavley, Joan Santelli, Bachir Sarr, Susan M. Sawyer

Bibliographic record

VenueThe Lancet · 2017
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Waterloo
FundersEconomic and Social Research Council
KeywordsMalnutritionInvestment (military)Consolidation (business)MedicineChild developmentDiseaseDevelopmental psychologyEconomic growthPsychologyPediatricsEconomicsPolitical scienceFinance

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0090.002

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 head0.084
GPT teacher head0.347
Teacher spread0.263 · 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

Citations246
Published2017
Admission routes1
Has abstractno

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