{"id":"W6920353461","doi":"10.6068/dp14ba7c4a75355","title":"Trend 2007 - 2011. Statistics Canada. CANSIM: Culture and Leisure - Film and Video | Country: Canada | Table: Film and video distribution, operating expenses, by North American Industry Classification System (NAICS) | Variable: Advertising, marketing and promotions, Motion picture and video distribution | Units: %, 2007-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-046.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Official statistics; Economic statistics; Population; Summary statistics; Descriptive statistics; Entertainment; Distribution (mathematics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006049451,0.0007171842,0.0007681539,0.00005057839,0.0006614533,0.0005884387,0.0008414541,0.0004825395,0.00009206874],"category_scores_gemma":[0.0001775158,0.0006887052,2.634416e-7,0.0003262314,0.0003906014,0.0007786994,0.0007600604,0.001071718,0.000002299042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000320844,"about_ca_system_score_gemma":0.001857671,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9544114,"about_ca_topic_score_gemma":0.9152917,"domain_scores_codex":[0.9955598,0.0005511173,0.000823379,0.001715923,0.0006921668,0.0006576076],"domain_scores_gemma":[0.99601,0.0005914455,0.000960413,0.001583379,0.0001880883,0.0006666979],"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":[0.00002128726,0.00002523268,0.0004994613,0.0004301065,0.00006977667,0.00003644663,0.000004468662,0.00003425104,0.000005459857,0.0004390093,0.9974088,0.00102571],"study_design_scores_gemma":[0.0004453321,0.00005722013,0.0004516997,0.0001050802,0.0001860434,0.0003953142,0.0002744345,0.04608255,8.09743e-8,3.761653e-7,0.9513216,0.0006802811],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001229374,0.004989434,0.00621892,0.00002374295,0.0002266355,0.0009367735,0.9873886,0.0001139189,0.00008975709],"genre_scores_gemma":[0.0004321084,0.002171267,0.001103827,0.0001083426,0.0001879189,0.00005631946,0.9953131,0.00008540689,0.0005417311],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0460872,"threshold_uncertainty_score":0.9995564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01463524033040338,"score_gpt":0.2352434376031404,"score_spread":0.220608197272737,"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."}}