{"id":"W2968141854","doi":"10.1190/segam2019-3215375.1","title":"Missing sonic log prediction using convolutional long short-term memory","year":2019,"lang":"en","type":"article","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Term (time); Long short term memory; Computer science; Speech recognition; Artificial intelligence; Recurrent neural network; Artificial neural network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002076168,0.0001032291,0.0001089877,0.00007030767,0.0001736132,0.0001930619,0.0003060592,0.00006159498,0.0003451093],"category_scores_gemma":[0.000007140385,0.00009617207,0.00004952338,0.0001701579,0.0000379901,0.0008738301,0.0001495543,0.000108953,0.00007330762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007647245,"about_ca_system_score_gemma":0.0001874511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009330058,"about_ca_topic_score_gemma":0.00000156789,"domain_scores_codex":[0.9989363,0.00002451082,0.0001852413,0.0003358991,0.0002624956,0.0002555559],"domain_scores_gemma":[0.9995251,0.00002936279,0.00005225108,0.0002644745,0.00005724606,0.00007161525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002151155,0.000254111,0.2412333,0.0004129676,0.0001273081,0.00007515063,0.001841875,0.009513979,0.217742,0.02309128,0.004999833,0.5006866],"study_design_scores_gemma":[0.0003198654,0.00002737767,0.0409434,0.000148441,0.00001125561,0.0001388224,0.00003052688,0.9457095,0.01126939,0.0008360259,0.0003018213,0.0002636124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2944847,0.0001489242,0.6944667,0.0002271036,0.0005898681,0.00006620868,5.160405e-7,0.0001429587,0.009873053],"genre_scores_gemma":[0.969878,0.00000214232,0.02833433,0.0005068874,0.0001666704,0.000001218008,0.000002793508,0.000007366027,0.001100656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9361955,"threshold_uncertainty_score":0.3921783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02947853723511743,"score_gpt":0.2584251591023023,"score_spread":0.2289466218671849,"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."}}