{"id":"W6976205593","doi":"10.6068/dp14ba876780d54","title":"Trend 1997 - 2012. Statistics Canada. CANSIM: Transportation - Transportation by Air | Country: Canada | Table: Domestic and international itinerant movements, by type of operation, airports with NAV CANADA towers | Variable: Kitchener/Waterloo, Ontario, Domestic movements, Total itinerant movements | Units: #, 1997-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-195.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Economic statistics; Official statistics; Summary statistics; Statistical analysis; International comparisons; Air travel; Aviation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001809662,0.002590986,0.002614221,0.00849313,0.003114678,0.004760027,0.004835611,0.001466566,0.08177846],"category_scores_gemma":[0.01696912,0.001647091,0.002152355,0.04165615,0.0006269502,0.002816461,0.002267333,0.003004113,0.05437905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03996957,"about_ca_system_score_gemma":0.1027957,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9934592,"about_ca_topic_score_gemma":0.9912097,"domain_scores_codex":[0.9963797,0.0002305002,0.0003909009,0.0005252108,0.001565597,0.0009081708],"domain_scores_gemma":[0.9737335,0.0009813971,0.0008299267,0.0008640373,0.02237551,0.001215601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002076459,0.000005522028,0.001107449,0.0002279765,0.0000205189,0.000006777795,0.0000230799,0.0001316374,0.000008608075,0.0003644626,0.9966569,0.001426339],"study_design_scores_gemma":[0.0001483013,0.00001195676,0.02287286,0.0008966727,0.00007073572,0.00002773458,0.0005589576,0.000572925,0.0001665747,0.00068305,0.9739039,0.00008635857],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004932342,0.00003849005,0.00002384188,0.00008783832,0.00002391726,0.00001062098,0.999019,0.00005249313,0.00069443],"genre_scores_gemma":[0.0007316265,0.0002161304,0.0002950733,0.00009945168,0.0000151221,0.00009451964,0.995784,0.0001003462,0.002663722],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9182215,"threshold_uncertainty_score":0.2900009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01302981321903368,"score_gpt":0.229462733674706,"score_spread":0.2164329204556723,"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."}}