{"id":"W7162021733","doi":"10.82308/42826","title":"Skill of monthly and seasonal forecasts using a Canadian general circulation model","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Climate variability and models","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistical analysis; General Circulation Model; Research methodology","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":[0.001125282,0.0006050374,0.0005455618,0.001190771,0.0009930638,0.001735253,0.001223976,0.000732858,0.003022988],"category_scores_gemma":[0.006864903,0.000377183,0.0006362792,0.001726522,0.0003426993,0.0008243796,0.0005519384,0.0009146137,0.000539546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01197606,"about_ca_system_score_gemma":0.01880631,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9778035,"about_ca_topic_score_gemma":0.9719172,"domain_scores_codex":[0.9994802,0.00004856113,0.00002719117,0.0001430259,0.0001958022,0.0001052968],"domain_scores_gemma":[0.997995,0.0004062308,0.000137944,0.0001214462,0.001147853,0.0001915862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004073291,0.00008830162,0.1140188,0.0001050435,0.0002241985,0.0001294317,0.0001771929,0.8173111,0.002187299,0.002515913,0.01540045,0.04743503],"study_design_scores_gemma":[0.00005044399,0.00002308571,0.0545586,0.00002221826,0.00004457512,0.00001366886,0.00007547715,0.939325,0.0007342788,0.0005975813,0.004499211,0.00005580749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9461055,0.0009613454,0.01122648,0.00142637,0.0002637969,0.00007410926,0.01591466,0.001789614,0.02223806],"genre_scores_gemma":[0.9844158,0.0002901092,0.005003043,0.00007438203,0.0000191152,0.00001210364,0.007237744,0.0001110962,0.002836485],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02219647,"threshold_uncertainty_score":0.08689284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02082290073814205,"score_gpt":0.2498380966896374,"score_spread":0.2290151959514954,"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."}}