{"id":"W4362579547","doi":"10.1016/j.powtec.2023.118506","title":"Filtration of dust particles in underground coal mines","year":2023,"lang":"en","type":"article","venue":"Powder Technology","topic":"Aerosol Filtration and Electrostatic Precipitation","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China; Tencent","keywords":"Filtration (mathematics); Cartridge; Particle (ecology); Coal; Coal mining; Particle size; Environmental science; Materials science; Process engineering; Petroleum engineering; Waste management; Engineering; Geotechnical engineering; Geology; Mechanical engineering; Mathematics; Chemical 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":[0.00006360581,0.00005837825,0.00009199775,0.0002434802,0.00001489163,0.000005804294,0.00006078271,0.00009332356,0.00002108387],"category_scores_gemma":[0.00005392083,0.00006339094,0.00001208276,0.0006467363,0.00004300054,0.00007958509,0.000008541327,0.00006334361,0.00003939852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002203529,"about_ca_system_score_gemma":0.000009876981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006050722,"about_ca_topic_score_gemma":0.0001884205,"domain_scores_codex":[0.9995235,0.000008649886,0.0001799513,0.00007656141,0.00005769029,0.000153626],"domain_scores_gemma":[0.9998119,0.00004114405,0.00002063209,0.00009689799,0.00001790548,0.00001153949],"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":[0.00001572158,0.00005974132,0.03750686,0.0001067811,0.00003800717,0.000009811641,0.001110984,0.01848466,0.8766229,0.04343011,0.009192397,0.01342199],"study_design_scores_gemma":[0.001327652,0.0002083419,0.1018678,0.00005889177,0.00001871515,0.00001850613,0.003036493,0.2062058,0.6199282,0.06529421,0.001602772,0.0004326807],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992696,0.00006554698,0.004835376,0.001181874,0.00009364908,0.00008570372,0.000002896337,0.0005436534,0.0004953069],"genre_scores_gemma":[0.9994388,0.00004616784,0.0003675124,0.00001536315,0.000008770691,0.0000281941,0.0000212951,0.00001023491,0.00006372796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2566948,"threshold_uncertainty_score":0.2585008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01477756038502373,"score_gpt":0.2391644374050984,"score_spread":0.2243868770200746,"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."}}