{"id":"W6977137175","doi":"10.6068/dp14ba876260823","title":"Trend 2000 - 2011. Statistics Canada. CANSIM: Population and Demography - Births and Deaths | Country: Canada | Table: Deaths, by cause, Chapter XX: External causes of morbidity and mortality (V01 to Y89), age group and sex | Variable: 80 to 84 years, Pedestrian injured in unspecified nontraffic accident, Females | Units: #, 2000-2011. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-159.","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; Population statistics; Population; Demographic statistics; Socioeconomic status; Mortality rate; Fertility; Official statistics; Economic 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":[0.002132985,0.002305655,0.002605129,0.006352864,0.003096173,0.004111772,0.00497042,0.001403739,0.1015421],"category_scores_gemma":[0.01575462,0.001727185,0.002107959,0.02937817,0.0005557328,0.002078555,0.002299914,0.003099268,0.05433915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04590642,"about_ca_system_score_gemma":0.1133177,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9942951,"about_ca_topic_score_gemma":0.9928726,"domain_scores_codex":[0.9971948,0.0002392308,0.0003670271,0.000383037,0.00116501,0.0006508953],"domain_scores_gemma":[0.9742962,0.0009046425,0.0006632647,0.0007649645,0.02205771,0.001313289],"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":[0.00002554885,0.000006168933,0.0009961958,0.0002787925,0.00002129767,0.000007139932,0.00002795599,0.0001204973,0.000009219373,0.0003245856,0.9958891,0.002293579],"study_design_scores_gemma":[0.0002509082,0.00001594279,0.02707591,0.001233745,0.00009029905,0.00004111102,0.0005726417,0.0007532974,0.0001877901,0.0009191365,0.9687464,0.0001128371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006194438,0.00005951703,0.00003928216,0.000138323,0.00003615259,0.00002535101,0.9985317,0.00007878819,0.001028945],"genre_scores_gemma":[0.001085215,0.0003747374,0.0006548001,0.0002186431,0.00002212831,0.000225038,0.992928,0.0001412961,0.004350134],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1015421,"threshold_uncertainty_score":0.339692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04020771616065998,"score_gpt":0.2721434433053381,"score_spread":0.2319357271446781,"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."}}