{"id":"W2365906439","doi":"10.1145/2939672.2939846","title":"MANTRA","year":2016,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Trajectory; Scalability; Mantra; Computer science; Disjoint sets; Set (abstract data type); Intuition; Data mining; Algorithm; Mathematics; Combinatorics","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":[0.001282341,0.001209098,0.001286849,0.001846429,0.0007869052,0.002787105,0.003277805,0.001344983,0.01320286],"category_scores_gemma":[0.008549131,0.0006245492,0.001736211,0.002450036,0.000775381,0.005798891,0.002156848,0.001676545,0.009148029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007111599,"about_ca_system_score_gemma":0.00155988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003380601,"about_ca_topic_score_gemma":0.006024324,"domain_scores_codex":[0.9984531,0.0002981308,0.0001223449,0.0006324816,0.0003622475,0.0001316997],"domain_scores_gemma":[0.9969989,0.0009752723,0.0002767176,0.001216217,0.0003977272,0.0001352334],"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":[0.0006371613,0.0002863848,0.007897236,0.0009455482,0.0001951279,0.000553659,0.0004900558,0.09126364,0.006504216,0.1047416,0.06916513,0.7173202],"study_design_scores_gemma":[0.00006703437,0.000278255,0.001315616,0.0001313943,0.00008986603,0.001037622,0.0002489496,0.7644703,0.005993132,0.08624407,0.1400609,0.00006288048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02696629,0.003379885,0.9109926,0.00158225,0.0006527704,0.0004312732,0.003550223,0.0336871,0.01875766],"genre_scores_gemma":[0.2132357,0.001680766,0.7523425,0.001005542,0.0004020887,0.0003969433,0.00912987,0.001516253,0.02029034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01320286,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00816835984099675,"score_gpt":0.1822175770075888,"score_spread":0.1740492171665921,"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."}}