{"id":"W4405701616","doi":"10.37105/iboa.241","title":"Study of the internal environment quality monitoring system for a laboratory model of a mining separator at key sensitive points of operation and process control using artificial intelligence","year":2024,"lang":"en","type":"article","venue":"Inżynieria Bezpieczeństwa Obiektów Antropogenicznych","topic":"Mining and Industrial Processes","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Computer science; Automation; Feed forward; Process (computing); Separator (oil production); Engineering; Control engineering; Mechanical engineering; Artificial intelligence; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008236844,0.0001986812,0.0004581146,0.00002850488,0.0001887022,0.00004486636,0.000200104,0.0001241595,0.00001063945],"category_scores_gemma":[0.0001438002,0.00009113061,0.0001020225,0.0002151208,0.0001549767,0.0001450529,0.0001004293,0.0001121699,5.828576e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009243899,"about_ca_system_score_gemma":0.00007675053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001629432,"about_ca_topic_score_gemma":0.00004410425,"domain_scores_codex":[0.9979972,0.000217679,0.0008353639,0.0003922003,0.0003494475,0.0002081357],"domain_scores_gemma":[0.9988737,0.000371527,0.0004016323,0.0001007292,0.0001929999,0.00005938812],"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":[0.0006088199,0.0001950415,0.006515126,0.0002291917,0.0001603493,0.000001440338,0.004519282,0.005566245,0.9802526,0.0002274415,0.00000232886,0.001722168],"study_design_scores_gemma":[0.0004125467,0.0009733854,0.002179135,0.0005101927,0.000249528,0.000009028356,0.03273277,0.07497121,0.8875996,0.0000920364,0.000006809532,0.0002637252],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997551,0.0002183793,0.0006826882,0.00004432463,0.0002643416,0.0007849314,0.000420102,0.00002110254,0.0000131625],"genre_scores_gemma":[0.9995472,0.000008177932,0.0001929495,0.000004163699,0.0002010611,0.00003187037,0.000003608623,0.000004299981,0.000006704927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09265293,"threshold_uncertainty_score":0.3716199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09266708000930268,"score_gpt":0.3198107406991968,"score_spread":0.2271436606898941,"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."}}