{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001295674,0.0001509298,0.0001652679,0.00004699708,0.000289025,0.0003176967,0.002279435,0.0000488709,0.0000151599],"category_scores_gemma":[0.0001467909,0.0001366109,0.00006899618,0.0003538092,0.00003094904,0.0005888439,0.0005354178,0.001631639,0.0001238926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001649401,"about_ca_system_score_gemma":0.001649155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002222541,"about_ca_topic_score_gemma":0.00005748478,"domain_scores_codex":[0.997035,0.0001096649,0.0002515155,0.0004447836,0.0003121757,0.001846824],"domain_scores_gemma":[0.9986989,0.00004265024,0.0001286401,0.0008267001,0.00005275398,0.0002502894],"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":[0.00004905223,0.00009880518,0.0004657602,0.00001975521,0.0002352545,0.0001650833,0.001986901,0.00075977,0.002904948,0.4655547,0.02348996,0.50427],"study_design_scores_gemma":[0.003354721,0.001527,0.0002781373,0.0001016154,0.0001373516,0.006431788,0.002789689,0.4889614,0.0009830934,0.2850105,0.2087459,0.001678827],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04656544,0.002573893,0.9401242,0.008817621,0.0006239208,0.00008183315,0.000002144866,0.0002107134,0.001000284],"genre_scores_gemma":[0.9938893,0.0003213763,0.00231527,0.001891377,0.00136598,6.20412e-7,0.00000424579,0.00001748229,0.0001942935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9473239,"threshold_uncertainty_score":0.7088752,"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."}}