{"id":"W2405031239","doi":"","title":"Enrichissement du OLAP pour l'analyse géographique : exemples de réalisation et différentes possibilités technologiques.","year":2005,"lang":"fr","type":"article","venue":"EDA","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Online analytical processing; Computer science; Data warehouse; Database","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":[0.004660957,0.001184286,0.0007418165,0.0021728,0.001018071,0.004775959,0.001427766,0.001896438,0.00404947],"category_scores_gemma":[0.01484776,0.0005832782,0.00118719,0.003417755,0.001228544,0.005479747,0.002098558,0.002220402,0.001492534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007731252,"about_ca_system_score_gemma":0.00142312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00947946,"about_ca_topic_score_gemma":0.007544024,"domain_scores_codex":[0.9948887,0.001559612,0.000313162,0.0005238121,0.002552574,0.000162117],"domain_scores_gemma":[0.9876797,0.006943089,0.0003292237,0.002474909,0.002335629,0.0002374514],"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":[0.001367359,0.0005841515,0.01077201,0.001742487,0.0003871518,0.002255033,0.005147232,0.0482229,0.064569,0.04334825,0.01182095,0.8097834],"study_design_scores_gemma":[0.0002836522,0.0004553465,0.01324113,0.000604276,0.0003664893,0.004306168,0.00421708,0.5369985,0.1364637,0.07153642,0.2312474,0.0002799029],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09040151,0.002011534,0.8805624,0.002314321,0.0001609472,0.000315773,0.001932244,0.008350646,0.01395069],"genre_scores_gemma":[0.2369915,0.001299321,0.7559653,0.0001537449,0.00007698203,0.0001761787,0.001535374,0.0004737158,0.003327849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00947946,"threshold_uncertainty_score":0.0246498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02225733101069067,"score_gpt":0.307215458527041,"score_spread":0.2849581275163504,"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."}}