{"id":"W2063733855","doi":"10.1016/j.fuproc.2010.09.027","title":"Estimation of free-swelling index based on coal analysis using multivariable regression and artificial neural network","year":2010,"lang":"en","type":"article","venue":"Fuel Processing Technology","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Multivariable calculus; Artificial neural network; Regression analysis; Regression; Linear regression; Statistics; Index (typography); Proximate; Range (aeronautics); Swelling; Computer science; Mathematics; Biological system; Artificial intelligence; Chemistry; Materials science; Engineering; Composite material; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004971088,0.0004478061,0.00057787,0.0009878784,0.0002345883,0.0004703185,0.000382215,0.0003660575,0.0004908012],"category_scores_gemma":[0.001141692,0.0001968831,0.0004679162,0.0007995608,0.0001595164,0.0008709194,0.0002859102,0.0002799055,0.0001515834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002800678,"about_ca_system_score_gemma":0.0002678932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00297346,"about_ca_topic_score_gemma":0.00333183,"domain_scores_codex":[0.9997557,0.00004583268,0.00001766842,0.00005405371,0.0001029007,0.00002398756],"domain_scores_gemma":[0.9995209,0.0002040028,0.00008108356,0.00002618824,0.0001466403,0.00002115778],"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":[0.0006812009,0.0004489814,0.06061265,0.0002596737,0.0002325656,0.0002042056,0.0001158517,0.5243804,0.1310045,0.001426496,0.0006694567,0.279964],"study_design_scores_gemma":[0.000003988067,0.0000362752,0.00988854,0.000001326989,0.0000155133,0.00001544146,0.00000916483,0.9826388,0.007120869,0.0001975632,0.00006033503,0.00001210226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6547477,0.0002025792,0.3432069,0.00004494717,0.00002851463,0.00002971373,0.00009668082,0.0004301561,0.001212922],"genre_scores_gemma":[0.9863327,0.00005186303,0.01316702,0.000004480269,0.000007672263,0.00001064544,0.00006774111,0.00001417663,0.0003436318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00297346,"threshold_uncertainty_score":0.005912304,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01338780425195668,"score_gpt":0.2515444603552597,"score_spread":0.238156656103303,"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."}}