{"id":"W7075350465","doi":"","title":"A Practical Approach to Merging Multidimensional Data Models","year":2011,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data warehouse; Data integration; Data modeling; Star schema; Online analytical processing; Dimensional modeling; IDEF1X; Schema (genetic algorithms); Merge (version control); Data mapping","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01164571,0.001468783,0.0009830494,0.00418743,0.002456429,0.009776072,0.005430491,0.003446109,0.009679052],"category_scores_gemma":[0.01944562,0.002284912,0.003616254,0.006409279,0.002488625,0.01259822,0.01093877,0.005187946,0.003651647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002083048,"about_ca_system_score_gemma":0.00378166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002584629,"about_ca_topic_score_gemma":0.004599849,"domain_scores_codex":[0.9869561,0.003943831,0.001297293,0.001652546,0.0056632,0.0004870267],"domain_scores_gemma":[0.9906411,0.00181758,0.0004685089,0.00462741,0.00217336,0.0002720105],"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":[0.0001216979,0.0002412415,0.001641447,0.0007185722,0.0002212877,0.000565451,0.002294416,0.02555093,0.01176071,0.550943,0.01497069,0.3909705],"study_design_scores_gemma":[0.00008813779,0.0002142937,0.000707361,0.000390858,0.000141353,0.001715093,0.00172491,0.2282898,0.0271333,0.3832106,0.3561912,0.0001930771],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006909553,0.0000991519,0.996078,0.0003546572,0.00002914652,0.0001415636,0.00009260995,0.0007120283,0.001802],"genre_scores_gemma":[0.008456045,0.0001276848,0.9900602,0.00009858324,0.00001168757,0.00009436062,0.0002835329,0.00008093159,0.0007869977],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01164571,"threshold_uncertainty_score":0.06158918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04460142822920218,"score_gpt":0.1719445983423505,"score_spread":0.1273431701131483,"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."}}