{"id":"W4294891909","doi":"10.1145/3550284","title":"SAMoSA","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","topic":"Music and Audio Processing","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Smartwatch; Computer science; Activity recognition; Wearable computer; Rendering (computer graphics); Inference; Mobile device; Speech recognition; Wearable technology; Deep learning; Artificial intelligence; Power consumption; Power (physics); Embedded system","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":[0.0002266944,0.0001526206,0.0002034757,0.0001554827,0.0005279706,0.0001148543,0.003439222,0.00004959011,0.00001303093],"category_scores_gemma":[0.0004653308,0.0001081127,0.00006800031,0.0005472421,0.000171661,0.0004455078,0.006323908,0.0004941974,0.000002545075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006717077,"about_ca_system_score_gemma":0.00002804157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001180116,"about_ca_topic_score_gemma":3.114946e-7,"domain_scores_codex":[0.998859,0.000008705819,0.000192748,0.0003959246,0.0002963821,0.0002472508],"domain_scores_gemma":[0.9989664,0.000112721,0.0002800019,0.0005165029,0.0001074321,0.00001697082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001744441,0.0005293155,0.003680511,0.0002270767,0.0001257282,0.000005807926,0.004409725,0.0001634699,0.2375363,0.05771038,0.03610318,0.6593341],"study_design_scores_gemma":[0.0002858208,0.0009356586,0.0004537238,0.0001865209,0.00001342625,0.00008387367,0.009113097,0.000748781,0.8415421,0.1198051,0.0265408,0.00029108],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842743,0.0007745758,0.0001561783,0.007195531,0.0003402942,0.0003663684,0.000004606984,0.0006066023,0.006281514],"genre_scores_gemma":[0.996472,0.00007843391,0.002407682,0.0003396863,0.0000149281,0.0002684215,9.722644e-8,0.000009491087,0.000409236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.659043,"threshold_uncertainty_score":0.7882298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070621549785252,"score_gpt":0.236134222616252,"score_spread":0.2254280071183995,"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."}}