{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001944444,0.002543299,0.002970709,0.01025155,0.003664579,0.005622961,0.005595462,0.001588779,0.07754209],"category_scores_gemma":[0.01962239,0.001767171,0.002138764,0.04895796,0.0007273704,0.002989183,0.002636538,0.003374097,0.05611503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05035008,"about_ca_system_score_gemma":0.1399303,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9926979,"about_ca_topic_score_gemma":0.9913661,"domain_scores_codex":[0.9952608,0.000268093,0.0005039439,0.0005857775,0.002281753,0.001099554],"domain_scores_gemma":[0.9554843,0.001516495,0.00121755,0.001158745,0.03881181,0.001810993],"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":[0.00001916811,0.000006185945,0.0009370203,0.000195724,0.00001728365,0.000006047582,0.00001736682,0.00009334261,0.000007529691,0.0003072966,0.9972934,0.001099614],"study_design_scores_gemma":[0.0001405468,0.00001156291,0.02155417,0.0008588853,0.00006776259,0.00002620348,0.0005715784,0.0005314931,0.0002021684,0.0006545496,0.975293,0.00008806449],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004764019,0.00003629515,0.00001785254,0.0001082225,0.00002281043,0.00001111246,0.9990687,0.00004650271,0.0006409169],"genre_scores_gemma":[0.000552602,0.000185233,0.0002423523,0.0001099781,0.00001498489,0.00008734499,0.9961727,0.00007392075,0.002560898],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07754209,"threshold_uncertainty_score":0.3653172,"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."}}