{"id":"W1539683852","doi":"10.1002/wcc.122","title":"Parameterizations: representing key processes in climate models without resolving them","year":2011,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Climate Change","topic":"Climate variability and models","field":"Environmental Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Closure (psychology); Climate model; Scale (ratio); Set (abstract data type); Stochastic modelling; Key (lock); Climate change; Statistical physics; Econometrics; Computer science; Mathematics; Geography; Statistics; Geology; Economics; Physics; Cartography","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001864759,0.0004501894,0.00073699,0.0001105331,0.0003805633,0.00007987586,0.0006812377,0.0001566753,0.002541198],"category_scores_gemma":[0.0001685607,0.0003801046,0.0001833719,0.0007758181,0.0002405595,0.001811719,0.00324073,0.0003063917,0.0007892261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001904249,"about_ca_system_score_gemma":0.000009241307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001255538,"about_ca_topic_score_gemma":0.0003864303,"domain_scores_codex":[0.996216,0.0002835993,0.001196156,0.001023878,0.0002879678,0.0009924261],"domain_scores_gemma":[0.9982759,0.0001082811,0.0004609731,0.0009550132,0.00002786125,0.0001719748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005913472,0.002344688,0.7033478,0.005334906,0.0000436446,0.0001366707,0.2471364,0.0008018492,0.001702104,0.001568834,0.0008901854,0.03610161],"study_design_scores_gemma":[0.00771686,0.002120444,0.1211967,0.07087991,0.001143633,0.0009540477,0.02246567,0.5436768,0.002452256,0.1797201,0.03404099,0.01363258],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8703022,0.003671811,0.0007891771,0.0004221832,0.0004444442,0.003894879,0.0001429004,0.0003427854,0.1199896],"genre_scores_gemma":[0.9402141,0.04985352,0.007453415,0.0003769147,0.000112807,0.001735999,0.00008925774,0.00008985741,0.00007413298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5821511,"threshold_uncertainty_score":0.9999888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2103598910523448,"score_gpt":0.3291765653431891,"score_spread":0.1188166742908443,"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."}}