{"id":"W2768750743","doi":"10.1007/s00704-017-2320-5","title":"Assessment of simulated and projected climate change in Pakistan using IPCC AR4-based AOGCMs","year":2017,"lang":"en","type":"article","venue":"Theoretical and Applied Climatology","topic":"Climate variability and models","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz; Department for International Development; International Development Research Centre","keywords":"Climatology; Precipitation; General Circulation Model; Environmental science; Climate change; Baseline (sea); Latitude; Representative Concentration Pathways; Climate model; Spatial distribution; Greenhouse gas; Atmospheric sciences; Geography; Meteorology; Mathematics; Statistics; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001270869,0.0006579834,0.0004322508,0.000725688,0.0006941831,0.001045004,0.0006724563,0.0009423533,0.00124782],"category_scores_gemma":[0.002369816,0.0003409323,0.0005391982,0.001315844,0.000466028,0.001038264,0.000408726,0.0005883555,0.0001994294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002335878,"about_ca_system_score_gemma":0.001692988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1164777,"about_ca_topic_score_gemma":0.06851374,"domain_scores_codex":[0.9996367,0.0001179804,0.00003105063,0.00007225975,0.00007067234,0.00007133887],"domain_scores_gemma":[0.9986369,0.0004825291,0.0001646938,0.0001126138,0.0005007256,0.0001026386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005654279,0.0002206966,0.09497731,0.0001550344,0.0002089081,0.0003684679,0.0001887144,0.8875725,0.001737462,0.001301193,0.002175494,0.01052881],"study_design_scores_gemma":[0.0002983908,0.0002574286,0.1470321,0.00004558755,0.0001805595,0.00008699686,0.0005609352,0.8450269,0.003180585,0.0009710201,0.002270951,0.00008855094],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916536,0.00009320929,0.000906484,0.0002652754,0.00004458008,0.00003828032,0.004401153,0.0001382282,0.002459252],"genre_scores_gemma":[0.9978576,0.00005675111,0.0006474823,0.00001289556,0.000007303458,0.00001688239,0.001270359,0.000007142075,0.0001236261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1164777,"threshold_uncertainty_score":0.2315995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02732777046235587,"score_gpt":0.3451125341696342,"score_spread":0.3177847637072784,"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."}}