{"id":"W6957873298","doi":"10.6068/dp14ba80a415d19","title":"Most Recent Data (2000). Statistics Canada. CANSIM: Society and Community - Rural Canada | Country: Canada | Table: Canadian Community Health Survey (CCHS 1.1) urban-rural profile, by sex | Variable: Injuries within past 12 months, Urban, Both sexes | Units: , 2000. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-189.","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; Official statistics; Population; Socioeconomic status; Rural area; Population statistics; Social statistics; Demographic statistics; Health 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":[0.002502762,0.002409175,0.00265938,0.008003101,0.004080604,0.004988195,0.005156751,0.001560924,0.1331857],"category_scores_gemma":[0.02124287,0.001881886,0.002040644,0.04546813,0.0007339196,0.002690212,0.002540578,0.003231385,0.07318273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07054324,"about_ca_system_score_gemma":0.1803837,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9962156,"about_ca_topic_score_gemma":0.9941639,"domain_scores_codex":[0.9947262,0.0003246378,0.0005772176,0.0005665046,0.002633794,0.001171519],"domain_scores_gemma":[0.9574872,0.001487049,0.001007117,0.001035956,0.03681238,0.002170316],"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":[0.00001651676,0.000006053514,0.0006766199,0.0001996574,0.00001074233,0.000005121432,0.00001902518,0.00006801987,0.000006274832,0.0002646369,0.9970633,0.001663959],"study_design_scores_gemma":[0.0001425967,0.00001267471,0.02480747,0.0009289487,0.00006158811,0.00002637342,0.0005370488,0.000322331,0.0001332191,0.0006084281,0.9723327,0.00008658164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005136177,0.00006995506,0.00002726219,0.0001637358,0.0000378857,0.00002371494,0.9978309,0.00006558678,0.001729642],"genre_scores_gemma":[0.001213575,0.0005755333,0.0006881593,0.0003402029,0.00002935781,0.0002144865,0.9876272,0.0001880487,0.009123505],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1331857,"threshold_uncertainty_score":0.5118294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03271055936016431,"score_gpt":0.2559629560472442,"score_spread":0.2232523966870799,"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."}}