{"id":"W4362724001","doi":"10.53063/synsint.2023.31139","title":"Recent advances in machine learning algorithms for sintering processes","year":2023,"lang":"en","type":"article","venue":"Synthesis and Sintering","topic":"Iron and Steelmaking Processes","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Sintering; Artificial intelligence; Machine learning; Materials science; Metallurgy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001818422,0.0001518045,0.0002063307,0.0001686046,0.00007973296,0.00006938686,0.00008624739,0.00004211066,0.00002345391],"category_scores_gemma":[0.0003070596,0.0001458045,0.00002682301,0.0002523779,0.00001893583,0.0001964578,0.00004228192,0.0001002609,0.000006348108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002922725,"about_ca_system_score_gemma":0.000007174569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002915555,"about_ca_topic_score_gemma":0.00007722345,"domain_scores_codex":[0.9992288,0.00001037713,0.0002022853,0.0001949322,0.00007070945,0.0002929405],"domain_scores_gemma":[0.9996333,0.0002156243,0.00002371039,0.00006394661,0.00002589182,0.00003749351],"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":[0.00002517848,0.000009829353,0.0007685648,0.001919968,0.00001548579,0.00001059426,0.000893926,0.01175059,0.003172999,0.00006421682,0.00002157963,0.9813471],"study_design_scores_gemma":[0.0003045799,0.00006361413,0.0006997192,0.001222598,0.00001433608,0.00001766656,0.001108305,0.2379633,0.04301974,0.0001014668,0.7150074,0.0004773192],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8008597,0.1233944,0.03761058,0.0007621452,0.002351552,0.00115295,0.00008367338,0.004746231,0.02903879],"genre_scores_gemma":[0.968949,0.02985102,0.0006498094,0.000009636681,0.00005709622,0.0001099295,0.000004209345,0.00004854648,0.0003207021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9808698,"threshold_uncertainty_score":0.5945736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02188518030967173,"score_gpt":0.2621959339688545,"score_spread":0.2403107536591828,"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."}}