{"id":"W2063278540","doi":"10.1145/2390045.2390054","title":"Towards intensional answers to OLAP queries for analytical sessions","year":2012,"lang":"en","type":"preprint","venue":"","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Online analytical processing; Computer science; Session (web analytics); Information retrieval; Extensional definition; Query language; Data cube; Cube (algebra); Database; Data mining; Data warehouse; World Wide Web","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003742703,0.0003375796,0.0005002976,0.0001678087,0.0001717712,0.0001110153,0.0007578284,0.0002011304,0.00007884268],"category_scores_gemma":[0.0003293094,0.000254748,0.0002268547,0.0001886902,0.00007877864,0.0004977294,0.003388473,0.0003143066,0.00006683612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008998526,"about_ca_system_score_gemma":0.0003874575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001730495,"about_ca_topic_score_gemma":0.00006009222,"domain_scores_codex":[0.9978719,0.00004468807,0.0004315434,0.000763864,0.0003694885,0.0005185679],"domain_scores_gemma":[0.9977274,0.0001477279,0.0001117018,0.001200005,0.0003872451,0.0004258983],"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":[0.00001882373,0.00004724227,0.00007665304,0.0001043514,0.00004478307,0.000004364996,0.000470108,0.0002548726,0.00007065941,0.9567707,0.0319065,0.01023091],"study_design_scores_gemma":[0.0002477794,0.00009958282,0.00102422,0.0003959169,0.00003700621,0.00003095948,0.0004069278,0.02565634,0.0008943941,0.008157916,0.9620538,0.0009951623],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005473119,0.0001274236,0.9884179,0.004210615,0.002688497,0.0006180006,0.0003035504,0.0002753472,0.002811317],"genre_scores_gemma":[0.03286613,0.0000103377,0.961431,0.001715946,0.0005235637,0.0003008335,0.0001746601,0.00002723787,0.002950249],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9486128,"threshold_uncertainty_score":0.9999905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05600656242751541,"score_gpt":0.3422436827572888,"score_spread":0.2862371203297734,"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."}}