{"id":"W2097003515","doi":"10.1002/cjce.20404","title":"Intelligent fitting of minimum spout‐fluidised velocity in spout‐fluidised bed","year":2010,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Nozzle; Support vector machine; Artificial neural network; Particle density; Particle (ecology); Materials science; Mathematics; Mechanics; Computer science; Engineering; Artificial intelligence; Thermodynamics; Mechanical engineering; Physics; Geology","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":[0.0007971415,0.0004681321,0.0006034528,0.000642073,0.0002725459,0.000533318,0.0005647845,0.0008010826,0.0006601913],"category_scores_gemma":[0.002930501,0.0003808866,0.0003558546,0.0003242188,0.0003015239,0.0005960861,0.0002364688,0.0004586726,0.0001830057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004814143,"about_ca_system_score_gemma":0.0004920679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005675559,"about_ca_topic_score_gemma":0.00321097,"domain_scores_codex":[0.9997587,0.00004836001,0.00001610523,0.00005006538,0.0000889424,0.00003786294],"domain_scores_gemma":[0.9992507,0.0004568918,0.00005276347,0.0000380392,0.0001783436,0.00002320171],"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":[0.0005194033,0.0001474084,0.01009411,0.0001877347,0.00003667105,0.000136931,0.0001559265,0.8638448,0.0602178,0.0007897034,0.0003147871,0.06355483],"study_design_scores_gemma":[0.000004404851,0.00003589823,0.001156915,0.000002677041,0.000002147535,0.000008085066,0.000009573339,0.988027,0.01060881,0.00007829244,0.00005978905,0.000006383681],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7549383,0.0001736768,0.2428201,0.00006759056,0.00003251454,0.00003210167,0.00007724931,0.0008768128,0.0009818058],"genre_scores_gemma":[0.9827819,0.00003402809,0.01684919,0.00000523249,0.000001414408,0.00001459059,0.00004076717,0.00001542856,0.0002575012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005675559,"threshold_uncertainty_score":0.01128507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008493858375193435,"score_gpt":0.1934089489489492,"score_spread":0.1849150905737558,"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."}}