{"id":"W6901335294","doi":"10.6068/dp14baa2bc08c67","title":"Trend 1972 - 2013. Statistics Canada. CANSIM: Population and Demography - Population Changes | Country: Canada | Province: Alberta | Table: Components of population growth | Variable: Births | Units: #, 1972-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-162.","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; Population growth; Social statistics; Economic statistics; 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":[0.002342303,0.00228005,0.00248958,0.008277142,0.003118237,0.004657256,0.004805053,0.001307416,0.121622],"category_scores_gemma":[0.01707359,0.00170512,0.001923842,0.03924643,0.0006205592,0.002190317,0.002395394,0.002940132,0.06756195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04830366,"about_ca_system_score_gemma":0.1254073,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9943843,"about_ca_topic_score_gemma":0.9925675,"domain_scores_codex":[0.9964156,0.0002322389,0.000371355,0.000441227,0.001779958,0.0007595928],"domain_scores_gemma":[0.9732891,0.0009569725,0.0006625105,0.0008858166,0.02280251,0.001403172],"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":[0.00001857725,0.000005034747,0.0008218071,0.0002160261,0.00001755852,0.000007045012,0.0000262278,0.0001333488,0.000009802358,0.0004164358,0.9958422,0.00248586],"study_design_scores_gemma":[0.0001494491,0.00001097024,0.02109988,0.0007115098,0.00005419418,0.00003012726,0.0004181998,0.0005087922,0.0001384907,0.000840935,0.975956,0.00008147887],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005611054,0.00006485484,0.00005538416,0.0001391179,0.00005125114,0.0000275137,0.9976598,0.0001191968,0.001826641],"genre_scores_gemma":[0.001114495,0.0003842997,0.0008490974,0.0001951553,0.00002784717,0.0002074171,0.9901636,0.0002241274,0.00683391],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.121622,"threshold_uncertainty_score":0.406866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02326454298074217,"score_gpt":0.2384486631389224,"score_spread":0.2151841201581802,"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."}}