{"id":"W1588334962","doi":"","title":"A comparison of different decision algorithms used in volumetric storm cells classification","year":2002,"lang":"en","type":"article","venue":"Fundamenta Informaticae","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Support vector machine; Computer science; Radar; Algorithm; Rough set; Data set; Statistical classification; Storm; Decision table; Data mining; Decision support system; Artificial intelligence; Machine learning; Decision rule; Set (abstract data type); Training set; Database; Meteorology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008314752,0.0009502414,0.00128932,0.003677558,0.000641025,0.001809555,0.001095396,0.001050921,0.0009944404],"category_scores_gemma":[0.02139894,0.0002670988,0.0009338328,0.003088447,0.0003321245,0.001562514,0.0005261429,0.0007466243,0.0005017847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009845551,"about_ca_system_score_gemma":0.0008055473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003664013,"about_ca_topic_score_gemma":0.002189895,"domain_scores_codex":[0.9936187,0.002721722,0.0008548835,0.0005427234,0.00191595,0.0003460591],"domain_scores_gemma":[0.9830341,0.01253028,0.0005224529,0.000786249,0.002955363,0.0001716351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001842076,0.000492457,0.0117208,0.0006379982,0.0004162765,0.0001028724,0.0003091158,0.0857806,0.004830444,0.003267901,0.00185014,0.8887493],"study_design_scores_gemma":[0.0002836322,0.002452848,0.01403028,0.0002304403,0.000553238,0.0003742407,0.0009362951,0.9396498,0.0287924,0.004877789,0.007710316,0.0001087263],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4449281,0.00593155,0.5343486,0.0005759192,0.000395856,0.0008879171,0.0008497301,0.001833185,0.01024914],"genre_scores_gemma":[0.6600692,0.001736654,0.3351999,0.0001284073,0.00007401466,0.0003153069,0.0009742502,0.00009131505,0.001410983],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008314752,"threshold_uncertainty_score":0.04397315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08031928922161695,"score_gpt":0.3013589145393605,"score_spread":0.2210396253177436,"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."}}