{"id":"W2010425666","doi":"10.1139/l03-025","title":"Mapping environmental conditions in the St. Lawrence River onto ice parameters using artificial neural networks to predict ice jams","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Meteorology; Geology; Environmental science; Computer science; Artificial intelligence; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0002766736,0.0002936882,0.0001457029,0.0005377984,0.0002099173,0.0004579847,0.0002276588,0.0002331901,0.0003416254],"category_scores_gemma":[0.001216763,0.0001183389,0.0001361769,0.0005220942,0.0001968733,0.0003717197,0.0002189198,0.0001983634,0.00006788422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001341147,"about_ca_system_score_gemma":0.0008393039,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1960976,"about_ca_topic_score_gemma":0.2806642,"domain_scores_codex":[0.9999332,0.00001546426,0.000004028263,0.00001249359,0.00001896173,0.00001580314],"domain_scores_gemma":[0.9996235,0.0001440856,0.00004952526,0.00001248672,0.0001464956,0.00002385826],"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":[0.0002067762,0.0001046118,0.1921942,0.00004044685,0.00005709444,0.0001746675,0.0001504059,0.7665991,0.001999322,0.0003226403,0.0006057797,0.03754491],"study_design_scores_gemma":[0.00001003663,0.00002900387,0.05157588,0.00000913006,0.00001244535,0.00001015549,0.0001284712,0.9464532,0.001266373,0.0002107043,0.0002848835,0.000009576857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964796,0.0000458745,0.002347223,0.00004831562,0.000005043392,0.000006897097,0.0001091457,0.00004956471,0.0009084897],"genre_scores_gemma":[0.9981788,0.00003055552,0.001289747,0.000005380445,0.000002111204,0.000004223804,0.0001452089,0.000002271719,0.0003415977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8039024,"threshold_uncertainty_score":0.3899124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166181290444464,"score_gpt":0.1747220154487253,"score_spread":0.1630602025442807,"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."}}