{"id":"W4246563707","doi":"10.1121/1.5031018.1","title":"10.1121/1.5031018.1","year":2018,"lang":"en","type":"dataset","venue":"Default Digital Object Group","topic":"Educational Robotics and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Acoustics; Kullback–Leibler divergence; Entropy (arrow of time); Bandwidth (computing); Mathematics; Random noise; Inverse; Speech recognition; Computer science; Physics; Statistics; Telecommunications","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001530599,0.005048606,0.003096544,0.003229758,0.002103124,0.01107215,0.00559694,0.01247413,0.8085063],"category_scores_gemma":[0.002225768,0.002022402,0.001390819,0.002992186,0.002165453,0.004045833,0.004527198,0.008241771,0.843272],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002558672,"about_ca_system_score_gemma":0.001603261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002604972,"about_ca_topic_score_gemma":0.001644562,"domain_scores_codex":[0.9980745,0.0001495559,0.0001237947,0.000671074,0.0005074511,0.0004736684],"domain_scores_gemma":[0.9984201,0.0002702911,0.0001917499,0.0002476131,0.000348801,0.0005214367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002110482,0.002221966,0.002865637,0.00535702,0.0001508863,0.001693662,0.0005020054,0.001616257,0.1012048,0.009077262,0.6186562,0.2545439],"study_design_scores_gemma":[0.0002650348,0.0001314,0.003857023,0.0006207783,0.00004859208,0.000657485,0.0002384309,0.003468162,0.006031267,0.001477596,0.9831527,0.00005160602],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.01447206,0.02978049,0.01903497,0.009288212,0.01792545,0.001356721,0.05909824,0.02909795,0.8199459],"genre_scores_gemma":[0.03571317,0.00760894,0.005795721,0.002165832,0.000599269,0.00110001,0.05944235,0.003725168,0.8838496],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.1914937,"threshold_uncertainty_score":0.2731425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009741029324410778,"score_gpt":0.2332038858557676,"score_spread":0.2234628565313568,"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."}}