{"id":"W7161953699","doi":"10.82308/31583","title":"Exploring population structure and migration with surnames : Quebec, 1621-1900","year":2004,"lang":"en","type":"dissertation","venue":"","topic":"Names, Identity, and Discrimination Research","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Census; Relevance (law); Diversity (politics); Spatial ecology; Urbanization; Multivariate 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002390919,0.000178909,0.000197065,0.0003249134,0.0007482392,0.0005554486,0.0001385778,0.0002017462,0.0003820552],"category_scores_gemma":[0.000163834,0.0001550109,0.00004272665,0.0003338557,0.00008092132,0.001137671,0.00001066629,0.0002284715,0.000005526082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002933187,"about_ca_system_score_gemma":0.0004728865,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.337765,"about_ca_topic_score_gemma":0.9605983,"domain_scores_codex":[0.9981581,0.0001154829,0.0002174169,0.0003298719,0.0009166801,0.0002624587],"domain_scores_gemma":[0.9992371,0.00004857163,0.0001496401,0.0001208202,0.0003127785,0.0001310843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003578962,0.0001885217,0.3615317,0.001321965,0.0001735188,0.00003058272,0.1105803,0.0001315053,0.0003797311,0.4095777,0.001755918,0.1139707],"study_design_scores_gemma":[0.0005989554,0.00006702219,0.9095833,0.0002688644,0.0001049042,0.000001173237,0.06938329,0.00001631327,0.0004978193,0.0146295,0.004245575,0.0006032903],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816517,0.0003398378,0.0000397286,0.000604687,0.0004236961,0.0004310294,0.00000876972,0.00008959328,0.016411],"genre_scores_gemma":[0.9561231,0.000847158,0.0002203164,0.00002011684,0.0002715297,0.00003628067,0.0009823119,0.00002294634,0.04147629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6228334,"threshold_uncertainty_score":0.6666449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06250794955234053,"score_gpt":0.343118606021489,"score_spread":0.2806106564691485,"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."}}