{"id":"W3096296438","doi":"","title":"Ensemble Prediction at the Canadian Meteorological Centre","year":2004,"lang":"en","type":"article","venue":"AGU Spring Meeting Abstracts","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Meteorology; Climatology; Environmental science; Geography; Remote sensing; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000680222,0.0001296172,0.0001229669,0.00006227399,0.000919333,0.0002507571,0.0004790612,0.00008370426,0.00001260094],"category_scores_gemma":[0.0002050507,0.00009293033,0.00008889315,0.0002449458,0.00004776438,0.0001970097,0.0001813651,0.0002095144,0.0001514526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002837438,"about_ca_system_score_gemma":0.0001070179,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.18509,"about_ca_topic_score_gemma":0.4779521,"domain_scores_codex":[0.9986064,0.00003419843,0.0002651826,0.0003445658,0.0002617933,0.0004879014],"domain_scores_gemma":[0.999126,0.00008312514,0.0001309743,0.0003961029,0.00005999379,0.0002038523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00001343718,0.00009455177,0.04286831,0.00002858938,0.0001710571,0.0003650753,0.002960548,0.8690482,0.00998435,0.02978736,0.0006695764,0.04400889],"study_design_scores_gemma":[0.001155391,0.0002050494,0.8386236,0.000299414,0.0001336622,0.0002259824,0.0003458566,0.04336989,0.04204819,0.00611175,0.06639708,0.001084176],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9556878,0.0001368457,0.001314831,0.004076232,0.0002995054,0.0001020065,0.000001749124,0.0001738625,0.03820718],"genre_scores_gemma":[0.9928784,0.000004534636,0.006498921,0.0002369208,0.0001181011,0.00000272972,0.000002106316,0.000007995144,0.0002502516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8256783,"threshold_uncertainty_score":0.8203366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01523132700998133,"score_gpt":0.2001582041014713,"score_spread":0.18492687709149,"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."}}