{"id":"W6901604610","doi":"10.6068/dp14baa275af845","title":"Trend 1998 - 2000. Statistics Canada. CANSIM: Labor - Industries | Country: Canada | Province: Alberta | Table: Construction industries, revenues and expenses, principal statistics by North American Industry Classification System (NAICS) | Variable: Building construction, Cost of construction materials and supplies | Units: $CAD x 1,000, 1998-2000. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-139.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Legal Cases and Commentary","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Census; Official statistics; Revenue; Summary statistics; Descriptive statistics; Principal (computer security); Index (typography)","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":[0.001841798,0.002429619,0.002536034,0.008647734,0.003237834,0.004713801,0.005307722,0.001512746,0.1006774],"category_scores_gemma":[0.0147958,0.001688497,0.001747353,0.04104354,0.0005863631,0.002298402,0.002105335,0.002748667,0.06862126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04500065,"about_ca_system_score_gemma":0.1045516,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9929898,"about_ca_topic_score_gemma":0.9911708,"domain_scores_codex":[0.9966503,0.000183432,0.000320764,0.0005015982,0.001524088,0.0008198466],"domain_scores_gemma":[0.9726309,0.0009815146,0.0008411335,0.0009101871,0.02326093,0.001375292],"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":[0.00002149771,0.000005514754,0.0009147163,0.0001895292,0.00001420542,0.000006183657,0.00001924278,0.00009660173,0.000009474814,0.000313989,0.9968029,0.001606051],"study_design_scores_gemma":[0.0001240937,0.00001024212,0.02020726,0.0006285588,0.00004615539,0.00002220032,0.0004082104,0.0003771398,0.0001513617,0.0006039363,0.9773549,0.00006590692],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004669792,0.00003511007,0.00002078936,0.00007926299,0.00002305699,0.0000107057,0.9989109,0.00005509716,0.0008183451],"genre_scores_gemma":[0.0005691299,0.0001724163,0.0002776703,0.00009254815,0.00001327795,0.00008265827,0.9950127,0.00008630485,0.003693303],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1006774,"threshold_uncertainty_score":0.3367994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01907066282416495,"score_gpt":0.2419155473229027,"score_spread":0.2228448844987377,"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."}}