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Record W4403143682 · doi:10.1016/j.clinme.2024.100253

Tackling climate change is a global medical community responsibility

2024· letter· en· W4403143682 on OpenAlexaffabout
Dr Husein Moloo, Dr Arnagretta Hunter, Ramesh Arasaradnam

Bibliographic record

VenueClinical Medicine · 2024
Typeletter
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsRoyal College of Physicians and Surgeons of Canada
Fundersnot available
KeywordsMedicineClimate changeEnvironmental resource managementEcology

Abstract

fetched live from OpenAlex

Tackling climate change is a global medical community responsibilityClimate change is no longer a distant threat, but a pressing reality that is significantly affecting human health. 1 With 2023 marked as the hottest year on record, 2 the projections are dire: the direct health impacts of climate change are projected to take 250,000 lives annually by 2050. 3 From extreme heat to flash flooding, climate change will affect everything from water security and food production 4 to patterns of infectious disease.No nation is immune, but the impact will be felt more by some than others.In this escalating global health emergency, the medical community's collaborative action is vital.As physicians, it is our duty to create change within our health systems and advocate for our patients' health.Despite being separated by thousands of miles geographically and two hemispheres, the Royal College of Physicians (RCP), the Royal College of Physicians and Surgeons of Canada (RCPSC) and the Royal Australasian College of Physicians (RACP) are closely united in tackling this issue.Their work should serve as a clarion call for health leaders worldwide.Physicians in Australasia have long advocated for climate health action.The RACP's extensive climate work 5 garners strong support and reflects its members' increasing concern about climate health impacts and the use and extraction of fossil fuels.The RACP has sought to bring health leaders together, establishing the Healthy Climate Future campaign, 6 which unites 13 medical colleges and numerous specialty societies.

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 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)0.011
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0030.010
Insufficient payload (model declined to judge)0.0280.007

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 head0.279
GPT teacher head0.489
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2024
Admission routes2
Has abstractyes

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