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Record W2886545044 · doi:10.1029/2018gl079133

On the Emergence of Anthropogenic Signal in Extreme Precipitation Change Over China

2018· article· en· W2886545044 on OpenAlexaff
Wei Li, Zhihong Jiang, Xuebin Zhang, Laurent Li

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsEnvironment and Climate Change Canada
FundersNational Key Research and Development Program of ChinaChina Scholarship CouncilNational Natural Science Foundation of ChinaAgence Nationale de la Recherche
KeywordsCoupled model intercomparison projectPrecipitationClimate changeEnvironmental scienceClimatologyChinaClimate modelClimate systemMeteorologyGeologyGeographyOceanography

Abstract

fetched live from OpenAlex

Abstract The detection of anthropogenic influences on climate extremes at regional scale is important for the development of national climate change policy. Global climate simulations from phase 5 of the Coupled Model Intercomparison Project under the Representative Concentration Pathway 8.5 scenario are used to examine the time at which an anthropogenic influence becomes detectable in extreme precipitation over China and the change in probability of extreme precipitation with certain magnitudes when the changes are detectable. Anthropogenic influence is not significantly detected over China in the observational record or simulations from 1961 to 2012 based on the test of field significance. Simulations indicate that such change would become detectable in the future by around 2035. Large changes would already manifest by the time of signal detection; for example, extreme precipitation events that occur on average once every 20, 50, and 100 years in current (1986–2005) climate would reduce to about 15, 34, and 63 years on average by the time of detection around 2035.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.136
GPT teacher head0.346
Teacher spread0.210 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations52
Published2018
Admission routes1
Has abstractyes

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