{"id":"W2970656788","doi":"","title":"LibGuides: Government Publications - Canada: Statistics: Suveys, Census & NHS","year":2009,"lang":"en","type":"libguides","venue":"","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Government (linguistics); Geography; Statistics; County government; Political science; Public administration; Demography; Sociology; Population; Mathematics","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":[0.00110088,0.001494389,0.0009119775,0.005907021,0.002580055,0.005071339,0.001292141,0.0007992263,0.2496309],"category_scores_gemma":[0.007990338,0.000871005,0.0005063371,0.02280526,0.0006677697,0.001983554,0.001270619,0.002141016,0.1108614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01788406,"about_ca_system_score_gemma":0.06376053,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.927536,"about_ca_topic_score_gemma":0.9429978,"domain_scores_codex":[0.9985519,0.0001038916,0.0001317545,0.0001377941,0.0008791198,0.0001955532],"domain_scores_gemma":[0.993792,0.0004802165,0.0002411482,0.0002536889,0.004921771,0.0003111144],"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":[0.00002899131,0.00001905959,0.001483758,0.0001307988,0.000005253177,0.00001765126,0.00009199644,0.0001340583,0.00002449747,0.002092089,0.9526035,0.04336839],"study_design_scores_gemma":[0.00001760703,0.000008266663,0.0130558,0.0003855291,0.00001055561,0.00003979761,0.000466666,0.0003206524,0.0002778604,0.0009474888,0.9844409,0.00002882354],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.004780115,0.007327009,0.001297613,0.005563057,0.001656621,0.0002084819,0.5305908,0.004373879,0.4442025],"genre_scores_gemma":[0.01399442,0.007694401,0.003998932,0.000661529,0.0002549771,0.0002730811,0.1626198,0.002712798,0.80779],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2496309,"threshold_uncertainty_score":0.8350985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0554818282421877,"score_gpt":0.3123401189691055,"score_spread":0.2568582907269178,"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."}}