{"id":"W3123173332","doi":"10.1126/sciadv.abc0671","title":"Making climate projections conditional on historical observations","year":2021,"lang":"en","type":"article","venue":"Science Advances","topic":"Climate variability and models","field":"Environmental Science","cited_by":308,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Environment and Climate Change Canada","funders":"H2020 Excellent Science; Environment Canada; Centre National de la Recherche Scientifique; European Commission","keywords":"Climatology; Computer science; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003162588,0.00006938414,0.00007069587,0.0000347821,0.0007716371,0.0000505585,0.0001879913,0.00001997445,0.0008585406],"category_scores_gemma":[0.000241858,0.00006403348,0.00003328011,0.0008602851,0.0004184406,0.0009267583,0.0001402418,0.00008425523,0.0001943931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006432288,"about_ca_system_score_gemma":0.00006745922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001557118,"about_ca_topic_score_gemma":0.00009392024,"domain_scores_codex":[0.9987159,0.00002163137,0.0001389018,0.0004025024,0.0004408972,0.000280108],"domain_scores_gemma":[0.9995906,0.00008043079,0.00004516139,0.0002072061,0.00002859496,0.00004797327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004634701,0.001643191,0.218062,0.00005489186,0.000008779786,0.00005165273,0.00167013,0.2421672,0.3403397,0.1642903,0.00296836,0.02869744],"study_design_scores_gemma":[0.0005127291,0.0002269525,0.284459,0.00008405814,0.00002526853,0.00008020802,0.0008434153,0.01333418,0.01745556,0.09673025,0.5854379,0.0008104552],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9101524,0.0001359327,0.004277634,0.004724337,0.001291716,0.0002502342,0.00005705314,0.0001602418,0.07895041],"genre_scores_gemma":[0.9906789,0.00002478353,0.007846598,0.000715742,0.00003016461,0.00003199371,0.000009150629,0.000004045361,0.0006586289],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5824695,"threshold_uncertainty_score":0.9400418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09461819489437354,"score_gpt":0.3336845307058741,"score_spread":0.2390663358115006,"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."}}