{"id":"W3013808434","doi":"10.1039/d0ew00104j","title":"A thermal imaging methodology to study evaporation kinetics in mine tailings","year":2020,"lang":"en","type":"article","venue":"Environmental Science Water Research & Technology","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cégep de Jonquière; Université de Sherbrooke","funders":"Bureau de l’Efficacité et de l’Innovation Énergétiques; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tailings; Mining engineering; Environmental science; Evaporation; Thermal; Kinetics; Geology; Materials science; Metallurgy; Geography; Meteorology; Physics","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":[0.001115972,0.0000958306,0.0001301274,0.0003171471,0.0001123729,0.00002865188,0.0005617601,0.00004052395,0.00006424033],"category_scores_gemma":[0.0001035867,0.00007709224,0.00001331553,0.001062815,0.00052812,0.0001047765,0.0005043136,0.000360624,0.0002408354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001280291,"about_ca_system_score_gemma":0.000005280416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002573178,"about_ca_topic_score_gemma":0.000005386304,"domain_scores_codex":[0.9984328,0.0001058962,0.0001748625,0.0003914609,0.0003334456,0.0005615987],"domain_scores_gemma":[0.9995723,0.0000363838,0.000007763771,0.0002453418,0.000009596615,0.000128611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003953116,0.00009184092,0.002692151,0.000001821228,0.000001621141,0.00001110021,0.001352635,0.001653398,0.969759,0.0000585435,0.00000383084,0.02437012],"study_design_scores_gemma":[0.0002390387,0.0003853595,0.02483981,0.00000259099,0.000002399913,0.000002761362,0.002782818,0.01016872,0.9588764,0.001829772,0.0007214183,0.0001488847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9901693,0.00001846766,0.003295995,0.005740741,0.00001979563,0.000551386,0.000001399743,0.00009859086,0.000104366],"genre_scores_gemma":[0.9841099,0.000002423642,0.01559856,0.00006185691,0.00002427008,0.0001806525,0.000001442969,0.00001305384,0.000007787115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02422124,"threshold_uncertainty_score":0.314373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0760190771565489,"score_gpt":0.3630448826847306,"score_spread":0.2870258055281817,"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."}}