{"id":"W3194315893","doi":"10.1007/s43670-023-00067-5","title":"Adaptive group Lasso neural network models for functions of few variables and time-dependent data","year":2023,"lang":"en","type":"article","venue":"Sampling Theory Signal Processing and Data Analysis","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of British Columbia; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial neural network; Lasso (programming language); Property (philosophy); Computer science; Constraint (computer-aided design); Matrix (chemical analysis); Algorithm; Nonlinear system; Penalty method; Function (biology); Set (abstract data type); Artificial intelligence; Mathematical optimization; Mathematics; Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001256299,0.0001679232,0.000351996,0.0001375554,0.0004545895,0.000137682,0.0003770595,0.00004550064,0.00006605106],"category_scores_gemma":[0.00001129027,0.0001458045,0.00005964754,0.0007077066,0.000101097,0.000575836,0.0005062398,0.0001317746,0.000001550606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003898158,"about_ca_system_score_gemma":0.00003202319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005837584,"about_ca_topic_score_gemma":0.000005156166,"domain_scores_codex":[0.99854,0.00009987342,0.0002922945,0.0006602776,0.0001412417,0.0002662803],"domain_scores_gemma":[0.9986188,0.0004489673,0.0001853822,0.0005889347,0.00006800647,0.00008994968],"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":[0.000242241,0.00005673369,0.0005392756,0.00005568027,0.001173355,3.36219e-7,0.0000966438,0.8193814,0.0001503432,0.009572956,0.001231071,0.1675],"study_design_scores_gemma":[0.0001948482,0.0000257667,0.00003769259,0.00003462335,0.001525946,5.673651e-7,0.000337349,0.9161226,0.000003502767,0.08141598,0.0001591029,0.0001420184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005416822,0.0006940687,0.9917331,0.00005525062,0.00003935193,0.0001256822,0.001708355,0.00006089154,0.0001664721],"genre_scores_gemma":[0.9882262,0.00003702821,0.004964765,0.00002762969,0.0003571554,0.00001298109,0.006032025,0.00002050125,0.0003217079],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9867684,"threshold_uncertainty_score":0.5945735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08933312037186174,"score_gpt":0.312323117612736,"score_spread":0.2229899972408743,"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."}}