{"id":"W3034247406","doi":"10.1016/j.coldregions.2020.103103","title":"River-ice blasting and explosive weight optimization for ice-flooding mitigation: A case study","year":2020,"lang":"en","type":"article","venue":"Cold Regions Science and Technology","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"National Key Research and Development Program of China; China Institute of Water Resources and Hydropower Research; National Natural Science Foundation of China","keywords":"Explosive material; Rock blasting; Wharf; Geology; Geotechnical engineering; Breakup; Impact crater; Environmental science; Flooding (psychology); Mining engineering; Hydrology (agriculture); Engineering; Marine engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002029475,0.00009505467,0.0001220815,0.0001669481,0.001063031,0.00006361072,0.0001577749,0.00006090558,0.00001211559],"category_scores_gemma":[0.0003097113,0.00008244944,0.00001110928,0.0009979794,0.00104871,0.000366915,0.00005353622,0.0001050443,0.000002085596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006017514,"about_ca_system_score_gemma":0.00009942622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006888908,"about_ca_topic_score_gemma":0.0001084054,"domain_scores_codex":[0.9990998,0.00001406822,0.0001351306,0.0003756794,0.0001381686,0.0002371735],"domain_scores_gemma":[0.99941,0.0001294715,0.00007510588,0.0001022542,0.000164566,0.0001185592],"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":[0.0000856091,0.0001809545,0.8450429,0.0001976482,0.00009303643,0.001714966,0.02561243,0.008370176,0.001475938,0.02088157,0.0004228333,0.09592196],"study_design_scores_gemma":[0.0008317287,0.0009721306,0.001172654,0.00003360815,0.00007627657,0.001238744,0.05123648,0.9421716,0.0002477551,0.001009689,0.0007362692,0.0002731187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769255,0.00008795704,0.01622481,0.005996091,0.000073598,0.0004725763,0.000009493768,0.00008557933,0.000124391],"genre_scores_gemma":[0.9885352,0.00006556237,0.01107988,0.000249875,0.00004244306,0.000008966139,0.000002894966,0.000002467604,0.00001265925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9338014,"threshold_uncertainty_score":0.8176079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02142497932288197,"score_gpt":0.2258154129704852,"score_spread":0.2043904336476032,"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."}}