{"id":"W4404200951","doi":"10.1016/j.mineng.2024.109093","title":"Multi-scale multi-task neural network combined with transfer learning for accurate determination of the ash content of industrial coal flotation concentrate","year":2024,"lang":"en","type":"article","venue":"Minerals Engineering","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakes Environmental (Canada); University of Waterloo","funders":"Fundamental Research Funds for the Central Universities","keywords":"Coal; Task (project management); Artificial neural network; Scale (ratio); Transfer of learning; Process engineering; Environmental science; Waste management; Computer science; Chemistry; Artificial intelligence; Engineering; Geography; Systems 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005995773,0.0005942106,0.0003561122,0.0004516162,0.0002360975,0.0003294588,0.0006028273,0.000724767,0.0007703116],"category_scores_gemma":[0.001009746,0.0002248571,0.0004359754,0.0003814873,0.0002484216,0.0008254538,0.0004172575,0.0005247631,0.0001820617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005869418,"about_ca_system_score_gemma":0.0005679406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008468474,"about_ca_topic_score_gemma":0.007569711,"domain_scores_codex":[0.9998497,0.00002868378,0.000008584103,0.00004343801,0.00004185643,0.00002772896],"domain_scores_gemma":[0.9997573,0.00008249842,0.00002955784,0.00002536976,0.00008813685,0.0000170222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003042365,0.0002434544,0.00466848,0.00008603256,0.00009530775,0.0001480766,0.00006253315,0.6559541,0.04650889,0.0008463701,0.001541107,0.2895414],"study_design_scores_gemma":[0.000002379058,0.00002248844,0.0005678152,9.967574e-7,0.000004694032,0.000006153698,0.000003863868,0.996696,0.002472193,0.0001430197,0.00007737213,0.00000308882],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4359255,0.000735845,0.5580417,0.0003555039,0.0001375695,0.00007623357,0.0001126299,0.001611702,0.003003413],"genre_scores_gemma":[0.9524953,0.00009539495,0.0458365,0.00006347151,0.00002613136,0.00003132616,0.00008626866,0.00001810901,0.001347509],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008468474,"threshold_uncertainty_score":0.01683837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05024371040197846,"score_gpt":0.2480888897878573,"score_spread":0.1978451793858789,"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."}}