{"id":"W6901635094","doi":"10.6068/dp14ba8b710737","title":"Trend 1991 - 2013. Statistics Canada. CANSIM: Construction - Residential Construction | Country: Canada | Table: Capital and repair expenditures, by sector and province | Variable: Other services (except public administration) (x 1,000,000), Capital, machinery and equipment | Units: $CAD, 1991-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-037.","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; Census; Official statistics; Summary statistics; Stock (firearms); Descriptive statistics; Public sector; Investment (military)","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":[0.001803962,0.00234535,0.002460773,0.00883707,0.0032317,0.004699037,0.004777643,0.001397954,0.09214644],"category_scores_gemma":[0.01627629,0.001651272,0.001919079,0.04021668,0.0006026019,0.002539625,0.002276657,0.002884314,0.05038996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05566248,"about_ca_system_score_gemma":0.1309027,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9952205,"about_ca_topic_score_gemma":0.9941714,"domain_scores_codex":[0.9957849,0.0002165895,0.0004066238,0.0005211636,0.002080958,0.000989834],"domain_scores_gemma":[0.9676411,0.001021092,0.001006504,0.000856928,0.02791791,0.001556471],"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":[0.00002377779,0.000007274737,0.001352087,0.0002629399,0.00002114223,0.000008346502,0.00002597191,0.0001380125,0.000009495432,0.0004789272,0.9956602,0.002011758],"study_design_scores_gemma":[0.0001226308,0.00001217031,0.02807721,0.0007593499,0.00006274254,0.000027614,0.0004742892,0.0004625751,0.0001702722,0.0006136301,0.9691399,0.00007774493],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007376856,0.00006043221,0.00002822243,0.0001225665,0.00002476443,0.00001392987,0.9985305,0.0000555092,0.001090262],"genre_scores_gemma":[0.001144677,0.0003488126,0.0003933824,0.0001357752,0.0000182077,0.0001095218,0.9924809,0.0001128237,0.005255896],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09214644,"threshold_uncertainty_score":0.4038615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01378635927636447,"score_gpt":0.2280863736364705,"score_spread":0.214300014360106,"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."}}