{"id":"W6920281112","doi":"10.6068/dp14ba7cc43238","title":"Most Recent Data (2005). Statistics Canada. CANSIM: Science and Technology - Innovation | Country: Canada | Table: Survey of innovation, logging and manufacturing industries, percentage of total revenue from the sale of products to selected industries | Variable: Sale of products to all other industries, Aerospace product and parts manufacturing, 0% of revenues, 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Revenue; Census; Product (mathematics); Official statistics; Summary statistics; Descriptive statistics; Publication; Unit (ring theory)","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":[0.002338019,0.002611287,0.002967934,0.01022667,0.004275853,0.005772423,0.005361157,0.001706286,0.1006456],"category_scores_gemma":[0.02341131,0.001820667,0.002052424,0.05457091,0.0007819601,0.002704859,0.002386505,0.003370834,0.06296517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06905244,"about_ca_system_score_gemma":0.1671074,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957765,"about_ca_topic_score_gemma":0.9939144,"domain_scores_codex":[0.994095,0.0003164247,0.0006550285,0.000641677,0.002933117,0.001358757],"domain_scores_gemma":[0.9486589,0.00190084,0.001365684,0.00119113,0.04482416,0.002059242],"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":[0.00001657521,0.000006626994,0.000761068,0.0002138572,0.00001325013,0.000005489216,0.00001801545,0.00008527374,0.000006817707,0.000261831,0.997403,0.001208148],"study_design_scores_gemma":[0.0001603133,0.00001298327,0.0256251,0.0008678477,0.00007319191,0.00002390887,0.0005897785,0.0003546332,0.0001659087,0.0005636918,0.9714736,0.00008897474],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004420564,0.00004613304,0.00001532615,0.0001156091,0.00002193695,0.00001134748,0.9989191,0.00004339286,0.0007829042],"genre_scores_gemma":[0.0007665044,0.0002889348,0.0003269268,0.0001758316,0.00001795058,0.0001072752,0.9940731,0.00008817267,0.004155295],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1006456,"threshold_uncertainty_score":0.5010129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04484154330595457,"score_gpt":0.257441385920074,"score_spread":0.2125998426141194,"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."}}