{"id":"W2293104209","doi":"10.1007/s00521-015-2093-7","title":"An artificial neural network model for predicting the CO2 reactivity of carbon anodes used in the primary aluminum production","year":2015,"lang":"en","type":"article","venue":"Neural Computing and Applications","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Aluminerie Alouette (Canada); Université du Québec à Chicoutimi","funders":"","keywords":"Anode; Materials science; Petroleum coke; Raw material; Coke; Carbon fibers; Reactivity (psychology); Artificial neural network; Calcination; Chemical engineering; Metallurgy; Composite material; Computer science; Chemistry; Electrode; Catalysis; Organic chemistry","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":[0.0006829822,0.00007245153,0.00008866636,0.00001105375,0.0002172732,0.00003165726,0.0001363009,0.00002948531,2.294607e-7],"category_scores_gemma":[0.00002550797,0.00005020069,0.00001759267,0.0001609363,0.0001548774,0.00009855632,0.00004972568,0.00008523278,2.635642e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003035227,"about_ca_system_score_gemma":0.000009487708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002811222,"about_ca_topic_score_gemma":0.0001855468,"domain_scores_codex":[0.999231,0.0001002229,0.0001842315,0.0002127228,0.000133982,0.0001378375],"domain_scores_gemma":[0.9995289,0.00009453081,0.0001234315,0.000214959,0.0000130455,0.00002511838],"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":[0.00004516761,0.00007913973,0.2200715,0.00001212521,0.000002616104,7.355801e-8,0.002030142,0.6820426,0.08195342,0.0001971313,0.00008768122,0.01347838],"study_design_scores_gemma":[0.00008936342,0.00003459457,0.06506213,0.000003768006,0.00001348957,0.00001156018,0.0003124792,0.931504,0.001312669,0.00156047,0.00003647856,0.00005900807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966085,0.000007539128,0.002097507,0.0003901651,0.0001166242,0.0006822244,0.00000366413,0.00003303498,0.0000607708],"genre_scores_gemma":[0.9988783,4.766728e-7,0.0006618896,0.00004303327,0.0003225918,0.00007419032,0.00001116296,0.000006721165,0.000001647313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2494614,"threshold_uncertainty_score":0.2047125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03589503515269739,"score_gpt":0.2626885132898374,"score_spread":0.22679347813714,"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."}}