{"id":"W6920735383","doi":"10.6068/dp14ba89868d072","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Seniors - Income, Pensions and Wealth | Country: Canada | Table: Survey of innovation, selected service industries, innovative business units using sources of information needed for suggesting or contributing to the development of innovation | Variable: Low importance, Computer systems design and related services, Consultancy firms | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-185.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Official statistics; Census; Economic statistics; Government (linguistics); Population; Summary statistics; Service (business); Investment (military); 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":[0.00216357,0.002308252,0.002682043,0.008619565,0.003465208,0.005223155,0.00524902,0.001607537,0.08748052],"category_scores_gemma":[0.01868402,0.001756877,0.002015664,0.04509029,0.0006714954,0.002367275,0.002521627,0.003197927,0.05581734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05309528,"about_ca_system_score_gemma":0.1250335,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9934522,"about_ca_topic_score_gemma":0.9915264,"domain_scores_codex":[0.9956593,0.0002324605,0.0005042159,0.0004765683,0.00201818,0.001109184],"domain_scores_gemma":[0.9590852,0.001495387,0.001338896,0.001037136,0.03510048,0.001942883],"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":[0.00001975652,0.000007758369,0.001062302,0.0002241981,0.00001411241,0.000006234048,0.0000210582,0.00007755879,0.000006422596,0.0002418931,0.9971283,0.00119044],"study_design_scores_gemma":[0.0001918707,0.00001465323,0.04046646,0.001033147,0.00007149473,0.00002597007,0.000694176,0.0003720307,0.0001911483,0.0005046269,0.9563378,0.00009661574],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005219466,0.00003315544,0.00001177699,0.00008640848,0.00001629199,0.00001194328,0.9991274,0.00003109394,0.0006297542],"genre_scores_gemma":[0.0007375529,0.0002226153,0.0002348304,0.0001265622,0.00001412488,0.0001210777,0.9947774,0.00006017551,0.003705582],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08748052,"threshold_uncertainty_score":0.385235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05756339453771658,"score_gpt":0.2353682375423605,"score_spread":0.1778048430046439,"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."}}