{"id":"W6912669858","doi":"10.5281/zenodo.3775611","title":"Census program data viewer, 2016 Census","year":2018,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Census; Geospatial analysis; Data visualization; Visualization; Product (mathematics); Presentation (obstetrics); Process (computing); Casual","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00166616,0.0009454501,0.000835109,0.00616651,0.0007076238,0.002896141,0.001617528,0.0006952739,0.2292803],"category_scores_gemma":[0.01599887,0.0007691255,0.0005515831,0.01832802,0.0002606177,0.002542934,0.001640526,0.001985928,0.0949939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003386058,"about_ca_system_score_gemma":0.01022549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2921939,"about_ca_topic_score_gemma":0.2939313,"domain_scores_codex":[0.9989194,0.0001666332,0.0001796505,0.0001263176,0.0004732858,0.0001346532],"domain_scores_gemma":[0.9917442,0.001125767,0.0005490439,0.0007137347,0.005209434,0.0006577487],"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":[0.00002396332,0.000005835012,0.0004883581,0.0001369398,0.000006291799,0.00001196398,0.00003876633,0.0001085229,0.00002620523,0.0009381439,0.9915412,0.006673746],"study_design_scores_gemma":[0.00004476844,0.000003402509,0.003404266,0.0001413767,0.000006540064,0.00003221697,0.0001073606,0.0002236026,0.00007716924,0.001110265,0.9948335,0.00001566069],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0001712485,0.0001175356,0.0005717356,0.0003680507,0.00007999179,0.00006830508,0.9816049,0.001657504,0.01536078],"genre_scores_gemma":[0.002761424,0.000600909,0.005136932,0.0003063914,0.00008070318,0.0003987465,0.9736539,0.002221508,0.01483953],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.2921939,"threshold_uncertainty_score":0.7670192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1062256077719555,"score_gpt":0.3397700493829557,"score_spread":0.2335444416110002,"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."}}