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Record W4283313907 · doi:10.1126/science.abo3378

Current global efforts are insufficient to limit warming to 1.5°C

2022· review· en· W4283313907 on OpenAlexaff
H. Damon Matthews, Seth Wynes

Bibliographic record

VenueScience · 2022
Typereview
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsGlobal warmingLimit (mathematics)Current (fluid)PoliticsInertiaNatural resource economicsEnvironmental scienceGlobal temperatureDevelopment economicsPolitical scienceClimate changeEconomicsEcologyOceanographyBiologyPhysicsMathematicsGeology

Abstract

fetched live from OpenAlex

Human activities have caused global temperatures to increase by 1.25°C, and the current emissions trajectory suggests that we will exceed 1.5°C in less than 10 years. Though the growth rate of global carbon dioxide emissions has slowed and many countries have strengthened their emissions targets, current midcentury net zero goals are insufficient to limit global warming to 1.5°C above preindustrial temperatures. The primary barriers to the achievement of a 1.5°C-compatible pathway are not geophysical but rather reflect inertia in our political and technological systems. Both political and corporate leadership are needed to overcome this inertia, supported by increased societal recognition of the need for system-level and individual lifestyle changes. The available evidence does not yet indicate that the world has seriously committed to achieving the 1.5°C goal.

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 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)0.002
metaresearch head score (Gemma)0.002
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.004

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 head0.076
GPT teacher head0.402
Teacher spread0.326 · 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

Citations502
Published2022
Admission routes1
Has abstractyes

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