{"id":"W6926952887","doi":"10.26050/wdcc/ar6.c6spccce","title":"IPCC DDC: CCCma CanESM5 model output prepared for CMIP6 ScenarioMIP","year":2019,"lang":"en","type":"dataset","venue":"World Data Center for Climate","topic":"Diatoms and Algae Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coupled model intercomparison project; Climate model; Earth system science; Climate change; Downscaling; Climate system; Grid","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001532178,0.001932376,0.001081267,0.003079571,0.0006442248,0.001999079,0.003137109,0.002017883,0.08403067],"category_scores_gemma":[0.004703198,0.0007818931,0.001619942,0.009326626,0.0003346172,0.002723629,0.001072092,0.002932467,0.04283156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003099115,"about_ca_system_score_gemma":0.003735944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09074298,"about_ca_topic_score_gemma":0.03600857,"domain_scores_codex":[0.9989733,0.0002192722,0.00006240573,0.0002021523,0.0004273451,0.0001155472],"domain_scores_gemma":[0.9982009,0.0002230096,0.000117517,0.0002512125,0.001097333,0.0001099323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001363128,0.0000334267,0.001135111,0.0005819335,0.0001040582,0.00003945255,0.00002712333,0.02355688,0.0002356769,0.003643762,0.9609842,0.009521926],"study_design_scores_gemma":[0.0003532452,0.00003679611,0.01044971,0.0003633065,0.0001023837,0.00004941948,0.0001325509,0.01953441,0.002252058,0.008911104,0.9576829,0.0001321048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00118591,0.000201104,0.002438316,0.0004517263,0.0004417118,0.0001428179,0.9793098,0.001436941,0.01439174],"genre_scores_gemma":[0.01895341,0.0004105871,0.008814071,0.0002968142,0.0001060919,0.001014798,0.9601017,0.001976458,0.008326111],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09074298,"threshold_uncertainty_score":0.2811106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1242170227199354,"score_gpt":0.376651304041664,"score_spread":0.2524342813217287,"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."}}