{"id":"W6920172648","doi":"10.6068/dp14ba8beb0fe18","title":"Trend 1994 - 2003. Statistics Canada. CANSIM: Culture and Leisure - Museums, Historic Sites, Archives and Other Heritage Institutions | Country: Canada | Table: Summary profile of heritage institutions and nature parks | Variable: Institutional or private capital revenues, Other museums | Units: , 1994-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-049.","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; Cultural heritage; Official statistics; Descriptive statistics; Population; Population statistics; Tourism; Publication","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":[],"consensus_categories":[],"category_scores_codex":[0.002501662,0.002613034,0.002765014,0.01088334,0.003592203,0.005903859,0.005848934,0.001562154,0.09360199],"category_scores_gemma":[0.02170289,0.001813761,0.002032573,0.0510298,0.0008053124,0.003018371,0.002483747,0.003416083,0.05796768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06114936,"about_ca_system_score_gemma":0.1691464,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954122,"about_ca_topic_score_gemma":0.9937278,"domain_scores_codex":[0.9943963,0.0003255481,0.0006075454,0.0007423258,0.002702158,0.001226114],"domain_scores_gemma":[0.9526823,0.001663169,0.00140017,0.00135631,0.04082607,0.00207188],"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":[0.00002055255,0.000005919248,0.00102088,0.0002087365,0.00001845371,0.000006183844,0.0000219949,0.0001007573,0.000008767442,0.0003663431,0.9967884,0.001433109],"study_design_scores_gemma":[0.0001170122,0.000009637532,0.02146344,0.0008064334,0.00006178066,0.00002253841,0.0005091588,0.0004624833,0.000155232,0.0006691765,0.9756445,0.00007861496],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000514346,0.0000488858,0.00002477511,0.0001382902,0.0000288781,0.000013695,0.9987143,0.00006258,0.0009170976],"genre_scores_gemma":[0.0008338209,0.0002777328,0.0003920101,0.0001630019,0.00001816042,0.0001230297,0.9937516,0.0001308668,0.004309708],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09360199,"threshold_uncertainty_score":0.4436717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02598718355783813,"score_gpt":0.2489628691358341,"score_spread":0.222975685577996,"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."}}