{"id":"W4401641666","doi":"10.3934/fods.2024036","title":"An over complete deep learning method for inverse problems","year":2024,"lang":"en","type":"article","venue":"Foundations of Data Science","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Inverse; Calculus (dental); Machine learning; Applied mathematics; Mathematics; Medicine; Geometry; Orthodontics","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":[0.0008945875,0.0007650564,0.0007169488,0.0005055346,0.0003121851,0.0007909419,0.0008560593,0.001096077,0.003304803],"category_scores_gemma":[0.002195432,0.0003815719,0.0006184233,0.0006185619,0.0009818475,0.001348356,0.001913749,0.002278721,0.0008306963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000512069,"about_ca_system_score_gemma":0.0009282394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001586124,"about_ca_topic_score_gemma":0.002827839,"domain_scores_codex":[0.999653,0.0001178762,0.00001368728,0.00005543282,0.000132842,0.00002713219],"domain_scores_gemma":[0.9995048,0.0002435034,0.00004171302,0.00008252848,0.00009172346,0.0000356951],"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":[0.000100934,0.00008144889,0.0004360957,0.0002916488,0.00008930784,0.0001256574,0.0001282466,0.5208248,0.01495464,0.2211497,0.008185546,0.233632],"study_design_scores_gemma":[0.000006378522,0.00002327626,0.00004039937,0.00001520708,0.000005682337,0.00003729471,0.000006781929,0.96942,0.0008523055,0.02613119,0.003455058,0.00000646872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001413159,0.0001939407,0.9969172,0.0001659952,0.00002577016,0.000008930721,0.00003029317,0.00007680924,0.001167872],"genre_scores_gemma":[0.1646945,0.001323972,0.8183477,0.0006014737,0.0002478715,0.0002071651,0.0003862897,0.0002099448,0.01398097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003304803,"threshold_uncertainty_score":0.01105571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0965615545278299,"score_gpt":0.3787573446347414,"score_spread":0.2821957901069115,"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."}}