{"id":"W2587179542","doi":"","title":"Centre of Population of Saskatchewan, Canada","year":2017,"lang":"en","type":"article","venue":"Thailand Statistician Thailand","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Population; Spatial variability; Demography; Physical geography; Statistics; Mathematics; Sociology","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":[0.0002853204,0.0005363618,0.000372583,0.002042106,0.003237443,0.001587541,0.001268395,0.0003168647,0.04949483],"category_scores_gemma":[0.001834593,0.0002398906,0.0003089539,0.005208028,0.0004397452,0.0005514162,0.0009086105,0.0008201544,0.006545166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01832635,"about_ca_system_score_gemma":0.05864574,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.987217,"about_ca_topic_score_gemma":0.9951475,"domain_scores_codex":[0.9993362,0.00006833128,0.00004495116,0.000126085,0.0002323247,0.000192176],"domain_scores_gemma":[0.9984073,0.00009771335,0.0000896304,0.00005817046,0.00107098,0.0002763226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002674152,0.00009497201,0.3274255,0.0008966718,0.0002351578,0.001895049,0.003405482,0.001474635,0.002274088,0.01277607,0.4439663,0.2052887],"study_design_scores_gemma":[0.00006092299,0.00005198094,0.6631393,0.0007130968,0.00009741892,0.001056872,0.01077575,0.001193541,0.000792761,0.00143197,0.3205456,0.0001406448],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2385385,0.009046667,0.003783505,0.007528953,0.0009167913,0.001157181,0.3226429,0.0006569657,0.4157286],"genre_scores_gemma":[0.5760516,0.008274157,0.007065548,0.003123769,0.0001013388,0.001060724,0.07499941,0.0001811917,0.3291422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04949483,"threshold_uncertainty_score":0.1655767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01285626446144779,"score_gpt":0.2718298526262536,"score_spread":0.2589735881648059,"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."}}