{"id":"W4408345561","doi":"10.1126/sciadv.adt8035","title":"Confronting Earth System Model trends with observations","year":2025,"lang":"en","type":"review","venue":"Science Advances","topic":"Climate variability and models","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Earth system science; Climate change; Climate model; Climate system; Climate science; Climatology; Position (finance); Computer science; Data science; Environmental science; Meteorology; Environmental resource management; Geography; Geology; Oceanography","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":[0.000725171,0.0002880958,0.000681593,0.0001590547,0.0005825174,0.0001179816,0.0009045152,0.00007661105,0.00006916621],"category_scores_gemma":[0.000066248,0.0001964527,0.0001189815,0.002183275,0.0009962845,0.001184419,0.0003322815,0.0001830305,0.00005322885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002851567,"about_ca_system_score_gemma":0.0003123939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004140695,"about_ca_topic_score_gemma":0.0001097025,"domain_scores_codex":[0.9976546,0.00004234437,0.0003873066,0.0008442835,0.0006014304,0.0004700285],"domain_scores_gemma":[0.9989489,0.0001254343,0.0002465595,0.0005660421,0.00002290292,0.00009015085],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001148609,0.0000219054,0.00002906141,0.002957773,0.000004430917,0.000001495251,0.00006173083,0.02429599,0.000006183869,0.002412312,0.00002143729,0.9701865],"study_design_scores_gemma":[0.00007574322,0.00002918809,0.00001205538,0.007285993,0.0001677411,0.000009740234,0.00009018018,0.02175878,0.000003118564,0.0001458408,0.9699957,0.0004259435],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003171424,0.9473845,0.004392696,0.00003021434,0.0002064192,0.0003772999,0.0000669268,0.0001280329,0.04738217],"genre_scores_gemma":[0.0001536612,0.9745274,0.01616506,0.00003798726,0.00001930991,0.0001649781,0.00002281982,0.00001643927,0.00889241],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9699742,"threshold_uncertainty_score":0.801111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06180846789384553,"score_gpt":0.320741688689522,"score_spread":0.2589332207956764,"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."}}