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Record W3209760672 · doi:10.1016/s0140-6736(21)01824-9

The Lancet and Financial Times Commission on governing health futures 2030: growing up in a digital world

2021· review· en· W3209760672 on OpenAlexaff
Ilona Kickbusch, Dario Piselli, Anurag Agrawal, Ran D. Balicer, Olivia Banner, M Adelhardt, Emanuele Capobianco, Christopher Fabian, Amandeep S. Gill, Deborah Lupton, Rohinton Medhora, Njide Ndili, Andrzej Ryś, Nanjira Sambuli, Dykki Settle, Soumya Swaminathan, Jeanette Vega Morales, Miranda Wolpert, Andrew Wyckoff, Lan Xue, Aferdita Bytyqi, Christian Franz, Whitney Gray, Louise Holly, Micaela Neumann, Lipsa Panda, Robert D. Smith, Enow Awah Georges Stevens, Brian Li Han Wong

Bibliographic record

VenueThe Lancet · 2021
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsCentre for International Governance Innovation
FundersDirektion für Entwicklung und ZusammenarbeitDeutsche Gesellschaft für Internationale ZusammenarbeitChildren's Investment Fund FoundationWellcome TrustFondation BotnarWorld Health Organization
KeywordsDigital healthDigital transformationFutures contractHealth carePolitical scienceBusinessEconomic growthEconomics

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)0.014
metaresearch head score (Gemma)0.041
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.008
Science and technology studies0.0020.004
Scholarly communication0.0090.010
Open science0.0020.004
Research integrity0.0130.015
Insufficient payload (model declined to judge)0.0160.004

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 head0.089
GPT teacher head0.368
Teacher spread0.279 · 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

Citations399
Published2021
Admission routes1
Has abstractno

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