{"id":"W3041065453","doi":"10.2139/ssrn.3554826","title":"NetEase Cloud Music Data","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Cloud computing; Computer science; Operating 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003769057,0.0007454459,0.0005651286,0.001935482,0.0009566584,0.00185084,0.001037342,0.0005488095,0.02991137],"category_scores_gemma":[0.003076107,0.0002387014,0.000472796,0.002898656,0.0003293612,0.001890128,0.001532106,0.0009042011,0.02438138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007870481,"about_ca_system_score_gemma":0.001315925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0260144,"about_ca_topic_score_gemma":0.03296591,"domain_scores_codex":[0.9993002,0.00003513585,0.00004115741,0.0001277033,0.0003616287,0.0001340958],"domain_scores_gemma":[0.998246,0.0001343462,0.00008166043,0.0006904192,0.0005569424,0.0002907548],"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":[0.001801921,0.0002927542,0.01094804,0.000439819,0.0001241466,0.0004744113,0.0001687124,0.004866979,0.01058269,0.005221852,0.8843047,0.08077407],"study_design_scores_gemma":[0.000381481,0.0001271964,0.02695046,0.0001004312,0.00005409101,0.000350109,0.0005154027,0.04200646,0.01548171,0.00750247,0.9064227,0.0001073187],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05989472,0.0007978558,0.009493648,0.002077901,0.001982199,0.0005391842,0.8160886,0.02441504,0.08471081],"genre_scores_gemma":[0.1591383,0.0006059904,0.01213345,0.0005572277,0.0004927971,0.0002106963,0.7964664,0.001523683,0.02887159],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02991137,"threshold_uncertainty_score":0.1000635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03451425314778028,"score_gpt":0.2385436921783314,"score_spread":0.2040294390305512,"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."}}