{"id":"W2584486467","doi":"10.1016/b978-0-08-097053-0.00004-2","title":"Particle Size Analysis","year":2015,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Hatch (Canada)","funders":"","keywords":"Grinding; Particle size; Gangue; Process engineering; Range (aeronautics); Materials science; Concentrator; Mill; Particle-size distribution; Environmental science; Mechanical engineering; Metallurgy; Computer science; Engineering; Composite material; Chemical engineering; Telecommunications","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001483231,0.0002651738,0.0004179799,0.00009023114,0.00004195525,0.0000508721,0.0001438308,0.0001899947,0.0003690215],"category_scores_gemma":[0.00001450058,0.0002522482,0.000196297,0.0000321768,0.00003327036,0.00002909796,0.00003359416,0.0002843325,0.0002934825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007310913,"about_ca_system_score_gemma":0.00002181054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.598081e-7,"about_ca_topic_score_gemma":0.00001586793,"domain_scores_codex":[0.9990808,0.000005280557,0.0002598272,0.0002081187,0.0002175984,0.0002283676],"domain_scores_gemma":[0.9994032,0.00003298982,0.00004908987,0.0003170431,0.00005103196,0.0001466032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002410578,0.000001624578,0.00001099141,0.0001061729,0.0007629471,0.00003250562,0.0002624161,0.002569563,0.00005811029,0.0007485148,0.0007969502,0.9946478],"study_design_scores_gemma":[0.0001137892,0.00001098159,0.000007305864,0.00009649755,0.0007403109,0.000004158725,0.000005194,0.001943824,0.00005975533,0.004030093,0.9925837,0.0004043872],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0006061708,0.002950012,0.00001019133,0.000009517988,0.0001788695,0.0000704485,0.00001331583,0.000291369,0.9958701],"genre_scores_gemma":[0.06780793,0.00002385329,0.0001387713,0.00003042335,0.0002453084,0.000007284036,0.000009522822,0.00007096905,0.931666],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9942434,"threshold_uncertainty_score":0.999993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02312056687116484,"score_gpt":0.2362279503570009,"score_spread":0.213107383485836,"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."}}