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Record W4403899685 · doi:10.1016/s0140-6736(24)01822-1

The 2024 report of the Lancet Countdown on health and climate change: facing record-breaking threats from delayed action

2024· review· en· W4403899685 on OpenAlexfundno aff
Marina Romanello, Maria Walawender, Shih-Che Hsu, Yasna Palmeiro-Silva, Daniel Scamman, Zakari Ali, Nadia Ameli, Denitsa Angelova, Sonja Ayeb‐Karlsson, Sara Basart, Jessica Beagley, Paul J. Beggs, Luciana Blanco-Villafuerte, Wenjia Cai, Max Callaghan, Diarmid Campbell‐Lendrum, Jonathan Chambers, Victoria Chicmana-Zapata, Lingzhi Chu, Troy J. Cross, Kim Robin van Daalen, Carole Dalin, Niheer Dasandi, Shouro Dasgupta, Robert Dubrow, Matthew J. Eckelman, James D. Ford, Olga Gasparyan, Georgiana Gordon‐Strachan, Michael Grubb, Samuel H Gunther, Ian Hamilton, Yun Hang, Risto Hänninen, Stella M. Hartinger, Kehan He, Julian Heidecke, Jeremy Hess, Louis Jamart, Harshavardhan Jatkar, Ollie Jay, Ilan Kelman, Harry Kennard, Gregor Kiesewetter, Patrick L. Kinney, Dominic Kniveton, Rostislav Kouznetsov, Pete Lampard, Jason Lee, Bruno Lemke, Bo Li, Yang Liu, Zhao Liu, Alba Llabrés‐Brustenga, Melissa Lott, Rachel Lowe, Jaime Martínez-Urtaza, Mark Maslin, Lucy McAllister, Celia McMichael, Zhifu Mi, James Milner, Kelton Minor, Jan C. Minx, Nahid Mohajeri, Natalie C. Momen, Maziar Moradi‐Lakeh, Karyn Morrisey, Simon Munzert, Kris A. Murray, Nick Obradovich, Megan B O'Hare, Camile Oliveira, Tadj Oreszczyn, Matthias Otto, Fereidoon Owfi, Frank Pega, Andrew J Perishing, Ana‐Catarina Pinho‐Gomes, Jamie Ponmattam, Mahnaz Rabbaniha, Jamie Rickman, Elizabeth Robinson, Joacim Rocklöv, David Rojas‐Rueda, Renee N. Salas, Jan C. Semenza, Jodi D. Sherman, Joy Shumake-Guillemot, Pratik Singh, Henrik Sjödin, Jessica Slater, Mikhail Sofiev, Cecilia Sorensen, Marco Springmann, Zélie Stalhandske, Jennifer Stowell, Meisam Tabatabaei, Jonathon Taylor, Daniel Tong, Cathryn Tonne, Marina Treskova, Joaquín Triñanes, Andreas Uppstu, Fabian Wagner, Laura Warnecke, Hannah Whitcombe, Carol Zavaleta-Cortijo, Chi Zhang, Ran Zhang, Shihui Zhang, Ying Zhang, Qiao Zhu, Peng Gong, Hugh Montgomery, Anthony Costello

Bibliographic record

VenueThe Lancet · 2024
Typereview
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
FundersMedical Research CouncilCanadian Institutes of Health ResearchCenters for Disease Control and PreventionNational Institutes of HealthEuropean Centre for Medium-Range Weather ForecastsInternational Energy AgencyUniversity of LeedsYmpäristöministeriöNortheastern UniversityHORIZON EUROPE Framework ProgrammeNuclear Safety and Security CommissionNational Research FoundationNational Aeronautics and Space AdministrationWorld Health OrganizationWellcome TrustUniversity College LondonEuropean CommissionUniversity of AlbertaMinisterio de Ciencia e InnovaciónGeorge Mason UniversityGeneralitat de CatalunyaNational Science FoundationUK Research and InnovationMassachusetts General HospitalNational Institute for Health and Care ResearchTsinghua UniversitySchmidt Family FoundationMinistry of Education, IndiaAlexander von Humboldt-Stiftung
KeywordsCountdownAction (physics)Climate changeMedicineGeographyHistoryEngineeringGeologyOceanography

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)0.013
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 score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0170.006

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 head0.312
GPT teacher head0.440
Teacher spread0.129 · 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

Citations693
Published2024
Admission routes1
Has abstractno

Explore more

Same venueThe LancetSame topicClimate Change and Health ImpactsFrench-language works237,207