{"id":"W2775640526","doi":"10.5281/zenodo.1417499","title":"The Music Listening Histories Dataset.","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Music and Audio Processing","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Active listening; Computer science; Speech recognition; Psychology; Communication","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":[0.0006334807,0.003135688,0.001583999,0.004184004,0.0009601264,0.001938674,0.00282786,0.002424475,0.05681503],"category_scores_gemma":[0.003335415,0.0005295436,0.001446586,0.004384303,0.0003796563,0.001343888,0.002873716,0.001615056,0.08030488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007347556,"about_ca_system_score_gemma":0.001208641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02039474,"about_ca_topic_score_gemma":0.06073178,"domain_scores_codex":[0.9992641,0.000125172,0.00008254952,0.0001839765,0.0002158583,0.0001283582],"domain_scores_gemma":[0.998455,0.0002997203,0.0001069642,0.0004621275,0.0003488308,0.0003272643],"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":[0.0001711043,0.00007081433,0.0009482672,0.0005726502,0.00004690847,0.0000713,0.00003497449,0.0002448371,0.000426319,0.000240652,0.9870963,0.0100758],"study_design_scores_gemma":[0.0003914704,0.00007402237,0.01043712,0.0003103438,0.00007293859,0.0002860698,0.0002358181,0.001652624,0.001382166,0.001194396,0.9838803,0.00008265892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009160546,0.0002435619,0.0002618206,0.0001152889,0.0001251512,0.00003483205,0.9939343,0.001957264,0.002411552],"genre_scores_gemma":[0.0009385454,0.00006569046,0.0005008314,0.00005152525,0.00002841332,0.00004654239,0.9971871,0.0001103014,0.001071129],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05681503,"threshold_uncertainty_score":0.1900652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05781499292877928,"score_gpt":0.2632945970038976,"score_spread":0.2054796040751183,"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."}}