{"id":"W2049257988","doi":"10.1145/2389686.2389693","title":"Exploring and analyzing documents with OLAP","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Online analytical processing; Computer science; Cluster (spacecraft); Information retrieval; Centroid; Data science; Data mining; World Wide Web; Data warehouse; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0000943747,0.00005413765,0.00006061718,0.00002991188,0.00006712887,0.00003062703,0.00006504352,0.000005161894,0.000005009901],"category_scores_gemma":[0.000003718055,0.00003567286,0.000005916039,0.0001017944,0.0000125186,0.003654266,0.0001153534,0.00002670438,0.00001138254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007285737,"about_ca_system_score_gemma":0.000004260158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004242595,"about_ca_topic_score_gemma":0.000007330086,"domain_scores_codex":[0.9995769,0.000009238071,0.00006020146,0.0001102128,0.0000777987,0.000165631],"domain_scores_gemma":[0.9996856,0.00001506608,0.00002082412,0.0001914697,0.00001114612,0.00007586633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003826633,0.00002018683,0.07734303,0.00002336665,0.00002126933,0.000005210017,0.001624781,0.00001086342,0.0005042091,0.8745043,0.0001084046,0.0458306],"study_design_scores_gemma":[0.002025136,0.0003516212,0.1507402,0.0003667904,0.00003189572,0.0003620445,0.002690268,0.004037077,0.03497097,0.0007275279,0.8018607,0.001835725],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1068972,0.0001896153,0.8903992,0.00004542747,0.00009533213,0.00003514166,3.735292e-7,0.00006847559,0.002269208],"genre_scores_gemma":[0.7680876,0.00002375733,0.2315455,0.000038742,0.00004508608,0.00001093803,5.925967e-7,0.000002988773,0.0002447406],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8737767,"threshold_uncertainty_score":0.2649255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06807361504051525,"score_gpt":0.2563572938635775,"score_spread":0.1882836788230623,"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."}}