{"id":"W6958089401","doi":"10.6068/dp14ba8ea2c0915","title":"Most Recent Data (2005). Statistics Canada. CANSIM: Science and Technology - Innovation | Country: Canada | Table: Survey of innovation, logging and manufacturing industries, percentage of plants with new machinery or equipment supplied from different locations | Variable: From Europe, Plants that bought new machinery or equipment, Navigational, measuring, medical and control instruments manufacturing, All plants | Units: %, 2005. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-181.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Health and Wellbeing Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Census; Official statistics; Publication; Summary statistics; Business statistics; Statistical analysis; Control (management); 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":[0.002483264,0.002641034,0.00312406,0.01024153,0.003843767,0.00565982,0.005325298,0.001699719,0.1005291],"category_scores_gemma":[0.02372913,0.00187215,0.002096533,0.05874912,0.0007591607,0.002639455,0.002400602,0.00333983,0.06250937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06366478,"about_ca_system_score_gemma":0.1602789,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9946421,"about_ca_topic_score_gemma":0.9921525,"domain_scores_codex":[0.9937256,0.00035654,0.00075005,0.0006784666,0.003105203,0.001384115],"domain_scores_gemma":[0.9463891,0.002109381,0.001464267,0.001226579,0.04669347,0.002117125],"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":[0.00001769965,0.000007089321,0.0007934724,0.0002310671,0.00001448768,0.000005346444,0.0000185154,0.00008690819,0.000006375697,0.0002481743,0.9974087,0.001162227],"study_design_scores_gemma":[0.0001857889,0.00001389126,0.0283666,0.0009057162,0.00007991568,0.00002372279,0.000606403,0.0003581941,0.0001683394,0.00055238,0.9686487,0.00009024785],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004124509,0.00004280336,0.00001501429,0.000100808,0.00002049253,0.00001170864,0.9990051,0.00004250271,0.0007203407],"genre_scores_gemma":[0.000663142,0.0002623378,0.000309745,0.0001637833,0.00001725314,0.0001147462,0.9944381,0.00008514205,0.003945748],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1005291,"threshold_uncertainty_score":0.4619225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08086778400343107,"score_gpt":0.3355248731437122,"score_spread":0.2546570891402811,"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."}}