{"id":"W6920173600","doi":"10.6068/dp14ba8d3392b94","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Science and Technology - Research and Development | 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: Moderately high importance, Surveying and mapping (except geophysical) servicesá, Trade fairs and exhibitions | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-182.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Official statistics; Census; Publication; Service (business); Business statistics; Big data; Descriptive statistics; Statistics education","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":[0.002757569,0.00263887,0.002915357,0.01034337,0.004036377,0.00575455,0.005446872,0.001855699,0.1092583],"category_scores_gemma":[0.02673176,0.002002427,0.002222445,0.06116548,0.0008679367,0.002816876,0.002545287,0.003648269,0.0667632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07151098,"about_ca_system_score_gemma":0.1921195,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953483,"about_ca_topic_score_gemma":0.9927555,"domain_scores_codex":[0.9934841,0.0003697605,0.0007700567,0.0006777004,0.003284607,0.001413817],"domain_scores_gemma":[0.9360513,0.002468148,0.001608421,0.001570047,0.05594,0.002362194],"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":[0.0000187108,0.000007722253,0.0008164384,0.0002390885,0.00001400071,0.000005473924,0.00001796262,0.00009390725,0.000007912517,0.0002691128,0.9972134,0.001296233],"study_design_scores_gemma":[0.000182974,0.00001275629,0.02805057,0.0009082988,0.00007260381,0.00002214259,0.0005959414,0.0003527966,0.0001849445,0.0006281104,0.9688928,0.00009599655],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004167185,0.00004126011,0.00001749199,0.0001218044,0.00002675088,0.00001617846,0.9987707,0.00004700473,0.0009171222],"genre_scores_gemma":[0.0008696687,0.0003302502,0.00044765,0.0002110161,0.00002105011,0.0001840951,0.9926641,0.0001159531,0.005156219],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1092583,"threshold_uncertainty_score":0.5188509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09810204468015415,"score_gpt":0.2939441413823942,"score_spread":0.1958420967022401,"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."}}