{"id":"W6957807477","doi":"10.6068/dp14ba83c9de513","title":"Trend 2002 - 2011. Statistics Canada. CANSIM: Construction - Residential Construction | Country: Canada | Table: Capital expenditures on construction, by type of asset and North American Industry Classification System (NAICS) sector | Variable: Student residences (x 1,000,000), Public administration | Units: $CAD, 2002-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-037.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Bone health and treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Census; Official statistics; Summary statistics; Stock (firearms); Asset (computer security); Index (typography); Descriptive statistics","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":[0.001587732,0.002417325,0.002381683,0.008278916,0.002801005,0.004755523,0.004610703,0.001369013,0.08731569],"category_scores_gemma":[0.01450816,0.001669539,0.001819754,0.03677026,0.0005572978,0.002430032,0.002098803,0.00271941,0.05523423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04582386,"about_ca_system_score_gemma":0.1003219,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9927955,"about_ca_topic_score_gemma":0.992007,"domain_scores_codex":[0.9963103,0.0001935288,0.0003554888,0.0004847672,0.001814025,0.0008419907],"domain_scores_gemma":[0.9707582,0.0009100328,0.0009436758,0.0008429576,0.02520941,0.001335695],"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":[0.00002194022,0.000007008586,0.001283909,0.0002029063,0.00001804559,0.000007187603,0.00002010393,0.0001285177,0.000008703489,0.0003690336,0.9962736,0.001659092],"study_design_scores_gemma":[0.0001186143,0.00001098713,0.02575521,0.0006514339,0.00005131701,0.00002565839,0.0004252654,0.0005221127,0.000182757,0.000540925,0.9716421,0.00007350744],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006462282,0.00004230638,0.00002341638,0.00008911038,0.00001937862,0.00001037875,0.9988441,0.00005641973,0.000850071],"genre_scores_gemma":[0.0008152366,0.0002236819,0.0002915652,0.00009475074,0.00001365902,0.00008225793,0.9943838,0.00009177515,0.004003223],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08731569,"threshold_uncertainty_score":0.3324769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03528429053449737,"score_gpt":0.2816277461230671,"score_spread":0.2463434555885697,"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."}}