{"id":"W6977104212","doi":"10.6068/dp14ba8c033c478","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Science and Technology - Innovation | 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: High importance, Other machinery, equipment and supplies wholesaler-distributors, Research and development staff | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-181.","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; Census; Official statistics; Business statistics; Publication; Service (business); Big data; Descriptive statistics; Social statistics","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":[0.002753297,0.002630994,0.003106447,0.01055468,0.004121619,0.005855868,0.005815853,0.001755541,0.1032218],"category_scores_gemma":[0.02483614,0.002091146,0.002254923,0.06214797,0.0008198707,0.002742958,0.00254665,0.003657972,0.0659723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07353842,"about_ca_system_score_gemma":0.184239,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9956079,"about_ca_topic_score_gemma":0.993261,"domain_scores_codex":[0.99343,0.0003672066,0.0007628245,0.0006780239,0.003287093,0.001475014],"domain_scores_gemma":[0.9369773,0.002295684,0.001605605,0.001470102,0.055173,0.002478238],"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":[0.0000197392,0.000008482328,0.0008863576,0.0002384159,0.00001418786,0.000005506349,0.00002149319,0.00008285206,0.000007333314,0.000251456,0.997142,0.001322135],"study_design_scores_gemma":[0.0002022736,0.00001504041,0.03608111,0.0009675891,0.0000827052,0.00002415359,0.0007247233,0.0003799993,0.0001887133,0.0005962596,0.960636,0.0001013569],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004563278,0.00003876495,0.0000170106,0.0001106367,0.00002238929,0.00001561874,0.9988508,0.00004719677,0.0008519145],"genre_scores_gemma":[0.0008051497,0.0002862384,0.0004051221,0.0001869405,0.00001910451,0.0001711367,0.9929121,0.0001122616,0.005101876],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1032218,"threshold_uncertainty_score":0.5335611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07848956767507424,"score_gpt":0.3017516597402845,"score_spread":0.2232620920652102,"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."}}