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Record W4413981196 · doi:10.1136/leader-2025-001262

4Ps framework: practical actions to protect individual health in the current climate crisis

2025· review· en· W4413981196 on OpenAlex
Hugh Montgomery, Amir Baniassadi, Wenjia Cai, Ali Kubba, Liang Li, Rossella E. Nappi, Amanda Stucke

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMJ Leader · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsImpactSt. Thomas Hospital
FundersBayer
KeywordsClimate changeGreenhouse gasExtreme weatherNatural resource economicsBusinessHealth careAction (physics)Environmental resource managementEnvironmental healthEnvironmental planningGeographyEnvironmental scienceMedicineEconomicsEcologyEconomic growthBiology

Abstract

fetched live from OpenAlex

Climate change driven by anthropogenic greenhouse gas (GHG) emissions represents an immediate and grave threat to human health and survival. Sea level rise, altered weather patterns and increasingly frequent and severe extreme weather events can damage health directly (eg, injury, heat stress, altered aeroallergen and particulate exposure). They also bring indirect health impacts through altered patterns of zoonotic and vectorborne diseases, disruption of food systems and downstream social consequences (economic collapse, mass migration and conflict).Healthcare providers and healthcare workers all need to take immediate action to drive and deliver reductions in GHG emissions, and to help patients in better managing the health impacts brought about by climate change. Here, we propose the '4Ps framework' (Personal, Professional, Pathway-specific and Policy) to empower and facilitate such action.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.835
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.449
GPT teacher head0.565
Teacher spread0.116 · 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