{"id":"W2559761937","doi":"10.5194/nhess-17-1033-2017","title":"River predisposition to ice jams: a simplified geospatial model","year":2017,"lang":"en","type":"article","venue":"Natural hazards and earth system sciences","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sinuosity; Geospatial analysis; Channel (broadcasting); Breakup; Geology; Digital elevation model; JAMS; Hydrology (agriculture); Physical geography; Geography; Geomorphology; Remote sensing; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005134969,0.0001590132,0.0001986395,0.00006744187,0.002070831,0.0004566399,0.0004506799,0.00007285926,0.00004198007],"category_scores_gemma":[0.00005402998,0.0001108492,0.00005149691,0.00009382614,0.000402336,0.0007215065,0.00005568822,0.0001346486,0.00007495413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005407658,"about_ca_system_score_gemma":0.00009758185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003379198,"about_ca_topic_score_gemma":0.001445686,"domain_scores_codex":[0.9984941,0.00003629161,0.0001954039,0.0004093454,0.0004731261,0.000391671],"domain_scores_gemma":[0.9993093,0.00005443273,0.0001336643,0.0002319008,0.00006679397,0.0002039057],"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":[0.0002378374,0.00002324121,0.133305,0.0002305986,0.0000449002,0.00004480186,0.003273762,0.02521925,0.0001470681,0.006309706,0.0004849243,0.8306789],"study_design_scores_gemma":[0.0001700653,0.000128189,0.190791,0.00008112646,0.00001413069,0.00003619514,0.0006665812,0.8075435,0.00001130426,0.0002334687,0.0001469891,0.0001773958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870213,0.0001230828,0.001563789,0.0006280581,0.0007730783,0.0002388405,0.00009994227,0.00005084016,0.009501104],"genre_scores_gemma":[0.9954315,0.00001819763,0.003690201,0.0002404266,0.0001969373,0.000001413129,0.0000139286,0.000002380024,0.0004050063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8305016,"threshold_uncertainty_score":0.9992284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01275720370406162,"score_gpt":0.2397648811929565,"score_spread":0.2270076774888949,"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."}}