{"id":"W2081487307","doi":"10.1007/s11004-010-9264-y","title":"Ore Grade Prediction Using a Genetic Algorithm and Clustering Based Ensemble Neural Network Model","year":2010,"lang":"en","type":"article","venue":"Mathematical Geosciences","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":82,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; McGill University","funders":"","keywords":"Artificial neural network; Resampling; Cluster analysis; Ensemble learning; Computer science; Ensemble forecasting; Kriging; Genetic algorithm; Artificial intelligence; Data mining; Machine learning; Algorithm; Pattern recognition (psychology)","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":[],"consensus_categories":[],"category_scores_codex":[0.0002055959,0.0001225126,0.0001321373,0.00004917822,0.0001976703,0.0001381416,0.0001109729,0.00006408486,0.00001404544],"category_scores_gemma":[0.00002829977,0.00009967809,0.00002401261,0.0001823941,0.0001091274,0.0001383532,0.00003404055,0.0001751236,0.000002291614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008394994,"about_ca_system_score_gemma":0.00001309132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000564598,"about_ca_topic_score_gemma":0.000006820688,"domain_scores_codex":[0.9991397,0.000008044636,0.0001813319,0.000178697,0.0001859941,0.000306285],"domain_scores_gemma":[0.9997112,0.00004208134,0.00002301807,0.0001047026,0.0000131139,0.0001058867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[5.357047e-7,0.000009590864,0.0001336937,0.0001016956,0.000002048395,0.000002095703,0.000156507,0.9852594,0.00656568,0.0000942702,0.00002195364,0.007652515],"study_design_scores_gemma":[0.00007726089,0.00001275436,0.0002121677,0.00004881155,0.00001115879,0.00003870023,0.00002252348,0.993268,0.0001604102,0.006022242,0.00001201417,0.0001140134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4813288,0.00003786546,0.5180008,0.00001683313,0.0001910584,0.00004914664,0.000001920103,0.000112911,0.0002606688],"genre_scores_gemma":[0.688949,0.000001556658,0.3108568,0.0000204625,0.0001164575,0.000005254841,5.159665e-7,0.00001103629,0.00003894372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2076202,"threshold_uncertainty_score":0.4064755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02446558296711545,"score_gpt":0.2421630346406421,"score_spread":0.2176974516735267,"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."}}