{"id":"W6976661236","doi":"10.6068/dp14baa342e783","title":"Trend 1990 - 2003. Statistics Canada. CANSIM: Manufacturing - General | Country: Canada | Province: Yukon | Table: Annual survey of manufactures (ASM), sales of manufactured goods by North American Industry Classification System (NAICS) and industry sub-sector | Variable: Manufacturing, Incorporated businesses with employees having sales of manufactured goods greater than or equal to $30,000 | Units: $CAD x 1,000, 1990-2003. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-149.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Economic statistics; Manufacturing; Official statistics; Summary statistics; Statistical analysis; Publication; Socioeconomic status; Statistical survey","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":[0.001549054,0.002326774,0.002786214,0.008365737,0.003092923,0.00437336,0.005139309,0.001465488,0.07471131],"category_scores_gemma":[0.01432397,0.001627049,0.001957897,0.04228285,0.0006260223,0.002264613,0.002044873,0.002700168,0.05424507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04698328,"about_ca_system_score_gemma":0.1166963,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944342,"about_ca_topic_score_gemma":0.9933544,"domain_scores_codex":[0.9965723,0.0002010127,0.0003897405,0.0005471459,0.001412633,0.0008771445],"domain_scores_gemma":[0.9735397,0.0008928092,0.0009516785,0.0008383624,0.02255637,0.001221132],"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":[0.00002490593,0.000005542983,0.001172469,0.0002362157,0.00002270387,0.000006846146,0.00001897729,0.00009867964,0.000008889617,0.0002644827,0.9969188,0.001221495],"study_design_scores_gemma":[0.0001816893,0.00001358477,0.03023388,0.0007620691,0.00008433589,0.00003347226,0.0005461186,0.0005102624,0.0001930122,0.0005570388,0.9668007,0.00008393791],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005700926,0.00004205857,0.00001487075,0.00008423542,0.00001970836,0.000008805342,0.9991384,0.00004608221,0.0005888465],"genre_scores_gemma":[0.0007514253,0.00017998,0.0001972861,0.0001058962,0.00001226893,0.00007009239,0.9960411,0.00006431867,0.002577527],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07471131,"threshold_uncertainty_score":0.3408891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03413170408400047,"score_gpt":0.2507878497632268,"score_spread":0.2166561456792264,"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."}}