{"id":"W2746930660","doi":"10.1007/s00382-017-3860-1","title":"High-resolution projections of mean and extreme precipitations over China through PRECIS under RCPs","year":2017,"lang":"en","type":"article","venue":"Climate Dynamics","topic":"Climate variability and models","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"","keywords":"Precipitation; Climatology; Environmental science; Representative Concentration Pathways; Forcing (mathematics); GCM transcription factors; Coupled model intercomparison project; Climate model; Radiative forcing; General Circulation Model; Climate change; Meteorology; Geology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002515881,0.0001294299,0.0001621495,0.00002340308,0.0006547039,0.0000711633,0.0002080385,0.00009578865,0.0003616572],"category_scores_gemma":[0.00006764581,0.0001236752,0.00005231962,0.00006654594,0.0004704619,0.0006391328,0.0003491488,0.0001052346,0.0000267434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001881198,"about_ca_system_score_gemma":0.000009826308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002725661,"about_ca_topic_score_gemma":0.00647387,"domain_scores_codex":[0.9989757,0.00003995384,0.0002491507,0.0003127653,0.0001747962,0.0002476542],"domain_scores_gemma":[0.9991021,0.00005334156,0.0002053377,0.0005744756,0.00001384293,0.00005087885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002626216,0.00202983,0.369998,0.0004471394,0.0001680223,0.000004555124,0.01426136,0.2001591,0.01014331,0.3940484,0.001208464,0.007269141],"study_design_scores_gemma":[0.0004880563,0.00008069244,0.5885898,0.0000371794,0.00006335913,0.000004165775,0.0002417967,0.3732986,0.00005427119,0.0367777,0.000150358,0.0002140607],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978648,0.00001031044,0.007872311,0.0004841941,0.0002175852,0.0003241005,0.0002158167,0.00004041079,0.01218726],"genre_scores_gemma":[0.9936597,0.0002675934,0.005671463,0.00002811346,0.00001788247,0.00002484422,0.00005677255,0.00001507917,0.0002585847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3572707,"threshold_uncertainty_score":0.5043327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03455420048087569,"score_gpt":0.2771914488274085,"score_spread":0.2426372483465328,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}