{"id":"W2978775535","doi":"","title":"Application and study of Support Vector Regression based on optimization of weighted coefficient","year":2007,"lang":"en","type":"article","venue":"Journal of Jilin Institute of Chemical Technology","topic":"Advanced Algorithms and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"PCL Construction (Canada)","funders":"","keywords":"Support vector machine; Regression analysis; Regression; Linear regression; Mathematics; Correlation coefficient; Mathematical optimization; Statistics; Computer science; Artificial intelligence","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":[0.00177048,0.0007286769,0.0009527807,0.0008302579,0.0002221114,0.0006820412,0.0007895752,0.0007055061,0.0008895815],"category_scores_gemma":[0.00497308,0.0002426531,0.0005240634,0.001051991,0.0003286742,0.001016167,0.0004295709,0.000925325,0.0002241503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000333813,"about_ca_system_score_gemma":0.0006255946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004351056,"about_ca_topic_score_gemma":0.001737154,"domain_scores_codex":[0.9987988,0.0004182913,0.00005633743,0.0001630165,0.0004831623,0.00008035552],"domain_scores_gemma":[0.9983245,0.0009295808,0.0001359449,0.00007475221,0.0005016581,0.00003364774],"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":[0.0001658161,0.0001027603,0.00426857,0.00029322,0.0001518764,0.0001821837,0.0000693671,0.7346457,0.01297177,0.01045731,0.001871,0.2348205],"study_design_scores_gemma":[0.000004517898,0.00003049438,0.0002886934,0.000004374707,0.000006315482,0.00001884121,0.000004302425,0.9974465,0.001500241,0.0004648008,0.0002257314,0.000005175894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04567513,0.0009978639,0.9514211,0.0001914963,0.00007597305,0.00003094056,0.00003136807,0.0002483856,0.001327702],"genre_scores_gemma":[0.8097948,0.001680436,0.1853597,0.00007061269,0.0001330471,0.0001323195,0.0002128954,0.00009597859,0.002520238],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004351056,"threshold_uncertainty_score":0.009363294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006121044783480368,"score_gpt":0.2529738296118167,"score_spread":0.2468527848283363,"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."}}