{"id":"W7081968020","doi":"10.11159/mmme25.154","title":"Process Optimization for Scheelite Flotation from A Low-Grade Sample","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Process optimization; Sample (material); Scheelite; Process (computing); Process control","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004652889,0.0004984297,0.0007188685,0.0003823191,0.0005022254,0.0007309316,0.0004454027,0.000643697,0.001471276],"category_scores_gemma":[0.0007093266,0.0002683393,0.0005557484,0.0003032133,0.0002171362,0.0003579299,0.0003014478,0.0005944459,0.000240594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006356712,"about_ca_system_score_gemma":0.0008383492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003547117,"about_ca_topic_score_gemma":0.006964887,"domain_scores_codex":[0.9998748,0.00001517075,0.000005573774,0.00002914817,0.00004355475,0.00003173808],"domain_scores_gemma":[0.9997726,0.0001289838,0.00002164239,0.0000117882,0.00005298168,0.00001187102],"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":[0.0007070843,0.0006642949,0.002231993,0.0004009961,0.00008533856,0.0002127297,0.0001109399,0.5095309,0.4359221,0.001437143,0.0007202575,0.04797621],"study_design_scores_gemma":[0.00008469138,0.00104198,0.002489849,0.000009264042,0.00005015109,0.00004102859,0.00006944063,0.8204095,0.1742512,0.0004523052,0.001081422,0.00001918282],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271055,0.0005749749,0.06842969,0.0002143555,0.00003455391,0.00008279745,0.0001668509,0.0002465358,0.00314477],"genre_scores_gemma":[0.963182,0.0002254738,0.03437504,0.00003200495,0.000008082647,0.00007532293,0.0001843861,0.00006758668,0.001850186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003547117,"threshold_uncertainty_score":0.007052898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00588650099011107,"score_gpt":0.2135004320165176,"score_spread":0.2076139310264066,"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."}}