{"id":"W4224229612","doi":"10.5194/tc-16-1447-2022","title":"Convolutional neural network and long short-term memory models for ice-jam predictions","year":2022,"lang":"en","type":"article","venue":"˜The œcryosphere","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Convolutional neural network; Support vector machine; Binary classification; Artificial intelligence; Snow; Perceptron; Machine learning; Deep learning; Artificial neural network; Meteorology","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":[0.000615437,0.001022537,0.0004350925,0.0005854029,0.0002998209,0.0006220147,0.0008308245,0.0008823524,0.001711118],"category_scores_gemma":[0.001380742,0.0002935391,0.0006237942,0.0006653335,0.0002357457,0.0006630342,0.0003785901,0.001299346,0.0003447725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001696515,"about_ca_system_score_gemma":0.001299593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1065158,"about_ca_topic_score_gemma":0.09067678,"domain_scores_codex":[0.9998664,0.00002000035,0.00001167589,0.00003873836,0.00002071219,0.00004240978],"domain_scores_gemma":[0.9995827,0.000162191,0.00005023542,0.00001671984,0.0001641804,0.00002395431],"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":[0.0002346538,0.0002059323,0.01181339,0.00007098604,0.0001243684,0.0001358434,0.00003769292,0.9232563,0.001984193,0.000907589,0.002765554,0.05846355],"study_design_scores_gemma":[0.000001841524,0.000007190742,0.0005695082,0.000002995938,0.000005267566,0.000001985936,0.000002971779,0.9989754,0.0002141574,0.0001538981,0.00006302627,0.000001724148],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8355706,0.004185771,0.1459705,0.001643871,0.0005900434,0.0001085289,0.00294672,0.00148985,0.007494124],"genre_scores_gemma":[0.9874566,0.0002960803,0.008308324,0.0001068021,0.00003604565,0.00004270008,0.001047137,0.00001698068,0.002689318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1065158,"threshold_uncertainty_score":0.2117917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02171895871480542,"score_gpt":0.2233891642905544,"score_spread":0.201670205575749,"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."}}