{"id":"W6976432142","doi":"10.6068/dp14ba8f821f942","title":"Most Recent Data (2003). Statistics Canada. CANSIM: Environment - Natural Resources | Country: Canada | Table: Survey of innovation, selected service industries, percentage of total revenues from the sale of products to the mining and/or forestry and/or forest products industries | Variable: Forestry and/or forest products industry, Electronic and precision equipment repair and maintenance, 50% to 74% of revenues, Non-innovative business units | Units: %, 2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-086.","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; Revenue; Official statistics; Natural resource; Census; Summary statistics; Descriptive statistics; 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":[0.002260416,0.002359681,0.002835234,0.009210506,0.003750055,0.005033135,0.005140455,0.001580075,0.08995093],"category_scores_gemma":[0.02017238,0.001766176,0.002157181,0.05269687,0.0007380163,0.002413236,0.002283013,0.003236474,0.05116571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06747138,"about_ca_system_score_gemma":0.1722869,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9965686,"about_ca_topic_score_gemma":0.9952629,"domain_scores_codex":[0.9948111,0.0002970529,0.0006165148,0.00058004,0.002538865,0.00115635],"domain_scores_gemma":[0.9516366,0.001751616,0.001228049,0.001134037,0.04233634,0.001913375],"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":[0.00001975747,0.000007604814,0.0009896085,0.0002478368,0.00001810975,0.000006125693,0.00001997929,0.0001054104,0.000007040524,0.0002797834,0.9971116,0.001187201],"study_design_scores_gemma":[0.000192792,0.00001322369,0.03257481,0.0009459829,0.00008816425,0.00002515844,0.0006284617,0.0004792804,0.0001798763,0.0006172667,0.9641567,0.00009825026],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005052835,0.00004799195,0.00001446094,0.0001174194,0.00002185251,0.00001237229,0.9988608,0.00003862776,0.000836006],"genre_scores_gemma":[0.0009929461,0.0003119659,0.0003500689,0.0001876901,0.0000170652,0.0001227061,0.993717,0.00008536932,0.004215303],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08995093,"threshold_uncertainty_score":0.4895414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03218746472561308,"score_gpt":0.2432199665336205,"score_spread":0.2110325018080074,"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."}}