{"id":"W4401857458","doi":"10.3390/hydrology11080126","title":"Review of River Ice Observation and Data Analysis Technologies","year":2024,"lang":"en","type":"article","venue":"Hydrology","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Centre For Cold Ocean Resources Engineering","funders":"Government of Canada","keywords":"Geology; Hydrology (agriculture); Remote sensing; Physical geography; Geography; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025763,0.00004792967,0.0001465993,0.00007605878,0.00002616635,0.00000578339,0.0001842514,0.00004624098,0.0002870333],"category_scores_gemma":[0.00007937203,0.00003570939,0.00002222212,0.0003967595,0.000161342,0.0001271841,0.0000415424,0.00007090594,0.00002365402],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":8.269128e-7,"about_ca_system_score_gemma":0.00001577571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005101375,"about_ca_topic_score_gemma":0.0003021246,"domain_scores_codex":[0.9995157,0.00002642552,0.0001240487,0.0001927102,0.00005394766,0.00008720018],"domain_scores_gemma":[0.9995523,0.0001332342,0.00003186251,0.0002586685,0.00001182995,0.00001209474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001011277,0.000008365601,0.6665273,0.002705973,0.0004833308,0.00002637294,0.0001996684,0.0002556395,0.00001010119,0.001307392,0.001719911,0.3267458],"study_design_scores_gemma":[0.00006515475,0.0001004786,0.2034334,0.0004960755,0.001179999,0.00004209176,0.0001216438,0.7091037,0.000003646282,0.005081198,0.08022105,0.0001515327],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6234075,0.3418097,0.009026824,0.01868962,0.000477617,0.0003394683,0.0006899331,0.0003870112,0.005172277],"genre_scores_gemma":[0.9423181,0.05412327,0.002398336,0.0006005149,0.00001197763,2.535981e-7,0.0004977898,9.903034e-7,0.00004874187],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7088481,"threshold_uncertainty_score":0.3142814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03153031686177611,"score_gpt":0.2643235714345819,"score_spread":0.2327932545728058,"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."}}