{"id":"W4286207865","doi":"10.1101/2022.07.20.500680","title":"On the Genes, Genealogies, and Geographies of Quebec","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi; McGill University; McGill Genome Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research","keywords":"Genetic genealogy; Genealogy; Population; Geography; Range (aeronautics); Metadata; Evolutionary biology; History; Demography; Biology; Sociology; Computer science; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005291922,0.0001672391,0.0002070118,0.001086551,0.001246797,0.001616242,0.0007890448,0.0003359255,0.006880711],"category_scores_gemma":[0.002773181,0.0001164318,0.0002311527,0.003254778,0.0005996156,0.0005756118,0.000420574,0.0003655747,0.000387002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01613458,"about_ca_system_score_gemma":0.009125724,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9921183,"about_ca_topic_score_gemma":0.9935951,"domain_scores_codex":[0.9997823,0.00005535815,0.000007212985,0.00006981254,0.00004050695,0.00004474851],"domain_scores_gemma":[0.998624,0.000336156,0.0001459926,0.0001297952,0.0006434599,0.0001206687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001663877,0.00006592963,0.7812357,0.0001513288,0.0002391415,0.0003204171,0.002540119,0.08858055,0.001229011,0.02189622,0.04430066,0.05927458],"study_design_scores_gemma":[0.00002948287,0.00002520166,0.7872995,0.0002286628,0.00009489998,0.0000833833,0.003258425,0.1426986,0.0005604025,0.003818826,0.06181091,0.00009166006],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9359745,0.000830319,0.003276856,0.00219949,0.00002369752,0.00004279914,0.04210014,0.0001648876,0.01538736],"genre_scores_gemma":[0.9844677,0.000300163,0.001696735,0.000139425,0.000004852447,0.00002054609,0.009454417,0.0000358131,0.003880264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01613458,"threshold_uncertainty_score":0.1170651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0131735160981683,"score_gpt":0.2297450606640032,"score_spread":0.2165715445658349,"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."}}