{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004884964,0.00005966471,0.00007025445,0.0001619653,0.0001385891,0.0001747943,0.0006335875,0.0000171121,0.0000224403],"category_scores_gemma":[0.00007704327,0.00005867215,0.00001462878,0.0004605911,0.0001348261,0.00167766,0.0001104976,0.00007356241,0.000007450613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002369223,"about_ca_system_score_gemma":0.00003991507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004901022,"about_ca_topic_score_gemma":0.0000505247,"domain_scores_codex":[0.9993635,0.00001225932,0.0001200956,0.0002353134,0.0001366987,0.0001321331],"domain_scores_gemma":[0.9992725,0.00009259051,0.00001733295,0.0005149999,0.00006681365,0.00003574767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002788266,0.00003099794,0.00009483173,0.0001387563,0.000035542,0.000001416231,0.0007725964,0.1231815,0.6973377,0.03455379,0.003381545,0.1404685],"study_design_scores_gemma":[0.00002807286,0.00002596222,0.0001082974,0.00004363028,0.00001053728,0.000002330211,0.00003105147,0.9358771,0.003127319,0.002125296,0.05854997,0.00007046921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005573892,0.00007280447,0.9926704,0.00002798925,0.0001818037,0.0001450026,0.00007242982,0.0004480761,0.0008075709],"genre_scores_gemma":[0.5348046,0.00001868567,0.4649136,0.00001086836,0.00003305569,0.000008414946,0.0001873892,0.00001084139,0.00001258389],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8126956,"threshold_uncertainty_score":0.2392581,"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."}}