{"id":"W4254895427","doi":"10.22215/etd/2010-09029","title":"OLAP for trajectories","year":2010,"lang":"en","type":"dissertation","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Online analytical processing; Computer science; Information retrieval; Data mining; Data warehouse","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":[0.0000888714,0.0001177885,0.000109119,0.00007956537,0.00006702984,0.0003854381,0.001275999,0.0001127991,0.00005947816],"category_scores_gemma":[0.00001867911,0.0001008468,0.0000656164,0.0000900135,0.000004482453,0.000496725,0.00004821549,0.0001056406,0.0000457363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004419851,"about_ca_system_score_gemma":0.00002584955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001439949,"about_ca_topic_score_gemma":0.0002186107,"domain_scores_codex":[0.9993219,0.000002769467,0.0001079265,0.0002949632,0.0001296971,0.0001427448],"domain_scores_gemma":[0.9994022,0.00002189751,0.00005723291,0.0004346401,0.00005619913,0.00002785858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007032016,0.00003555142,0.000006734503,0.00009932636,0.00004709843,0.000002437689,0.0004181934,1.28848e-7,0.0002527407,0.3131937,0.09203076,0.5939063],"study_design_scores_gemma":[0.0001908163,0.00003380722,0.0003145004,0.00001087719,0.00001671686,2.693789e-7,0.0001435199,0.002429796,0.002978243,0.006854324,0.9867278,0.0002993306],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0004646297,0.00007816921,0.5977336,0.0005499407,0.02947138,0.0007750094,0.0000430084,0.000668408,0.3702159],"genre_scores_gemma":[0.001029655,0.00004121802,0.3724727,0.0002241167,0.0008669657,0.000164784,0.004413133,0.00002878503,0.6207586],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.894697,"threshold_uncertainty_score":0.4112414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01249896302712996,"score_gpt":0.2690094075350616,"score_spread":0.2565104445079316,"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."}}