{"id":"W6901603440","doi":"10.6068/dp14ba8f7f9c125","title":"Trend 2008 - 2010. Statistics Canada. CANSIM: Culture and Leisure - Museums, Historic Sites, Archives and Other Heritage Institutions | Country: Canada | Table: Heritage institutions, operating expenses, by North American Industry Classification System (NAICS) | Variable: Amortization and depreciation of tangible and intangible assets, Non-commercial art museums and galleries | Units: %, 2008-2010. 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; Public use; Publication; Socioeconomic status","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":[0.001647349,0.002499784,0.002534993,0.009180763,0.002488698,0.004643913,0.005162713,0.001475241,0.07145118],"category_scores_gemma":[0.01675426,0.001592224,0.002025548,0.04167597,0.0006504516,0.002659283,0.00197132,0.003279845,0.04728718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0426554,"about_ca_system_score_gemma":0.1137026,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9912744,"about_ca_topic_score_gemma":0.9898767,"domain_scores_codex":[0.9962095,0.0001799795,0.0004300397,0.0005293485,0.001805491,0.0008456868],"domain_scores_gemma":[0.9659038,0.001190864,0.001209831,0.0008258814,0.02952311,0.001346555],"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":[0.00001877221,0.000006563754,0.001266861,0.0002058345,0.00001868745,0.000005448528,0.00001469608,0.0001152534,0.000008079865,0.000248134,0.9970897,0.001002066],"study_design_scores_gemma":[0.0001892461,0.00001290321,0.03167413,0.0009397253,0.00007742349,0.00002752699,0.0005366012,0.0006565522,0.0002078017,0.000611803,0.9649774,0.00008876909],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005900804,0.0000369929,0.0000139843,0.00008665113,0.00002310977,0.000008944944,0.9992041,0.00003945359,0.0005278202],"genre_scores_gemma":[0.0006585898,0.0001684889,0.0001834362,0.00009638957,0.00001542499,0.00007526382,0.9963177,0.00006092074,0.002423698],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07145118,"threshold_uncertainty_score":0.309488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03643973879769612,"score_gpt":0.2528403027537826,"score_spread":0.2164005639560865,"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."}}