{"id":"W6901536045","doi":"10.6068/dp14baa2afce092","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Births and Deaths | Country: Canada | Province: Ontario | Table: Estimates of deaths, by sex and age group | Variable: -1 to 14 years, Both sexes | Units: #, 1972-2013. 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; Fertility; Socioeconomic status; Economic statistics; Demographic analysis; 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":[],"consensus_categories":[],"category_scores_codex":[0.002292843,0.002037287,0.002521778,0.00715664,0.00331695,0.004360071,0.004398699,0.00124614,0.09822339],"category_scores_gemma":[0.0169167,0.001765609,0.00209611,0.03387193,0.0006191022,0.002172841,0.002317565,0.002922238,0.04972037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06207798,"about_ca_system_score_gemma":0.1492828,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9960955,"about_ca_topic_score_gemma":0.9948812,"domain_scores_codex":[0.9961904,0.0002723605,0.0004585142,0.0004458228,0.001766873,0.000866],"domain_scores_gemma":[0.9707857,0.0009108686,0.0007783253,0.0008071824,0.02516489,0.001552932],"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":[0.00002723358,0.000006302274,0.001177573,0.0003100271,0.00002411841,0.000008217427,0.00003558119,0.0001200444,0.00001236607,0.0004446506,0.9950949,0.002739008],"study_design_scores_gemma":[0.0001751053,0.00001471745,0.03256086,0.0009948793,0.00007987053,0.00003843136,0.0005335567,0.0005424614,0.0001755342,0.0007370891,0.9640532,0.00009422453],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007946013,0.00009544631,0.00005993636,0.0001837757,0.00005323022,0.00003518947,0.997572,0.00009990283,0.0018211],"genre_scores_gemma":[0.001869773,0.0006657935,0.001046235,0.0002950364,0.00003586571,0.0002770415,0.9868525,0.0002248634,0.008733011],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09822339,"threshold_uncertainty_score":0.4504094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01570982162501065,"score_gpt":0.2314194765422058,"score_spread":0.2157096549171952,"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."}}