{"id":"W6976056226","doi":"10.6068/dp14ba859857d59","title":"Trend 2001 - 2004. Statistics Canada. CANSIM: Seniors - Housing and Living Arrangements | Country: Canada | Table: Federal personnel engaged in science and technological activities, by major departments and agencies | Variable: Other departments and agencies, Research and development | Units: #, 2001-2004. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-184.","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; Official statistics; Population; Socioeconomic status; Population statistics; Publication; Summary 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002367684,0.002507862,0.002750957,0.008935945,0.003815679,0.005166586,0.005489381,0.001559994,0.1044005],"category_scores_gemma":[0.01865499,0.001875885,0.002173306,0.03877471,0.0006329712,0.002614255,0.002500119,0.003205769,0.05601134],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06215802,"about_ca_system_score_gemma":0.1502131,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954693,"about_ca_topic_score_gemma":0.9937056,"domain_scores_codex":[0.9953446,0.0002839274,0.00048112,0.0005417689,0.002266369,0.001082194],"domain_scores_gemma":[0.9603391,0.001198364,0.001101565,0.001051272,0.03428161,0.002028106],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002303996,0.000006593503,0.001111159,0.0002175414,0.00001845077,0.000006472088,0.00002517858,0.00009129705,0.00000759836,0.000377933,0.996329,0.001785849],"study_design_scores_gemma":[0.0001368332,0.00001512051,0.03049836,0.0009393471,0.00006962142,0.00002878767,0.0006078021,0.0004473648,0.0001672174,0.0006318289,0.9663666,0.00009108707],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006942388,0.00005674577,0.00002970132,0.0001484554,0.00003722898,0.00001954736,0.9984053,0.0000644652,0.001169059],"genre_scores_gemma":[0.001045287,0.0003444788,0.0004504838,0.000201033,0.00002396652,0.0001656912,0.9910987,0.0001312441,0.00653909],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9976323,"threshold_uncertainty_score":0.4509901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07084111213450352,"score_gpt":0.2873624481719005,"score_spread":0.216521336037397,"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."}}