{"id":"W6957989931","doi":"10.6068/dp14baa2d54ee25","title":"Most Recent Data (2005). Statistics Canada. CANSIM: Culture and Leisure - Film and Video | Country: Canada | Province: New Brunswick | Table: Film, television and video post-production, summary statistics, by North American Industry Classification System (NAICS) | Variable: Post-production and other motion picture and video industries, Operating expenses (x 1,000,000) | Units: , 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-046.","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; Official statistics; Economic statistics; Descriptive statistics; Population; Summary statistics; Entertainment; Population statistics","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":[0.002224939,0.002441005,0.0028102,0.008681886,0.003674842,0.005251446,0.005117755,0.001604583,0.0992521],"category_scores_gemma":[0.02193218,0.001589256,0.002039748,0.04625512,0.0007180198,0.002504059,0.002159956,0.003160155,0.06208295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05210064,"about_ca_system_score_gemma":0.1425358,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944464,"about_ca_topic_score_gemma":0.9930037,"domain_scores_codex":[0.9952271,0.0002836912,0.0005417613,0.0006227909,0.002290325,0.00103433],"domain_scores_gemma":[0.9557615,0.001887144,0.001156713,0.001169769,0.0382392,0.001785698],"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":[0.00001665116,0.000005952627,0.0007616515,0.00020252,0.0000140103,0.000005238407,0.000017093,0.00008598725,0.000006971622,0.000239677,0.9974906,0.001153683],"study_design_scores_gemma":[0.0001566484,0.00001123315,0.0235954,0.0007905862,0.00007070984,0.00002246163,0.0005286308,0.0003721101,0.0001537696,0.0005298068,0.973685,0.00008365454],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004355615,0.00004571991,0.00001609404,0.0001064595,0.00002308106,0.000009701123,0.9990195,0.00004205749,0.0006939101],"genre_scores_gemma":[0.0006859423,0.0002365286,0.000305654,0.0001441109,0.00001799954,0.00009112226,0.9947744,0.00007538885,0.003668881],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0992521,"threshold_uncertainty_score":0.3780184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02372578314764563,"score_gpt":0.2419529569158936,"score_spread":0.218227173768248,"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."}}