{"id":"W6976884163","doi":"10.6068/dp14ba85ddb4870","title":"Trend 2007 - 2011. Statistics Canada. CANSIM: Business, Consumer and Property Services - Information and Culture | Country: Canada | Table: Software development and computer services, sales by type of client based on the North American Industry Classification System (NAICS) | Variable: Sales to businesses, Computer systems design and related services | Units: %, 2007-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-011.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Census; Official statistics; The Internet; Publication; Publishing; Information system; Software; Personal computer; Service (business)","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":[0.0006210761,0.0005839837,0.0006964629,0.0001094355,0.0002667122,0.0005820423,0.001175582,0.0003417532,0.00002807418],"category_scores_gemma":[0.000008619855,0.0004039088,1.435067e-7,0.0003557154,0.0001483003,0.000502394,0.0005555167,0.0004926444,0.00001136466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001170022,"about_ca_system_score_gemma":0.004088661,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9880052,"about_ca_topic_score_gemma":0.8845984,"domain_scores_codex":[0.9968681,0.0003837392,0.0007933975,0.0008107783,0.0007240814,0.0004198684],"domain_scores_gemma":[0.9965556,0.0005343183,0.001017162,0.001179346,0.0003606047,0.000352922],"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":[0.00005568747,0.00002203288,0.0006255533,0.00429665,0.0001411404,0.00002698567,0.00003598654,0.0008875965,2.593293e-7,0.00005212174,0.9934458,0.0004102019],"study_design_scores_gemma":[0.0002986198,0.00006154185,0.0001855125,0.0003977549,0.0001061772,0.00007330908,0.0001996091,0.1936484,1.185082e-8,2.223332e-8,0.804589,0.0004399676],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001152932,0.002364741,0.002651884,0.00001412908,0.0005011287,0.0008323114,0.9934993,0.00008757484,0.00003736742],"genre_scores_gemma":[0.00007594808,0.0003121651,0.00710218,0.0005269345,0.00006534741,0.00001675454,0.9917336,0.00005671391,0.000110371],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1927608,"threshold_uncertainty_score":0.9998413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02142582685976984,"score_gpt":0.2125558752986526,"score_spread":0.1911300484388828,"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."}}