{"id":"W4378195027","doi":"10.1126/science.add5300","title":"On the genes, genealogies, and geographies of Quebec","year":2023,"lang":"en","type":"article","venue":"Science","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi; McGill University; McGill Genome Centre","funders":"","keywords":"Population; Genealogy; Metadata; Genetic genealogy; Geography; Range (aeronautics); Evolutionary biology; Population genetics; Genetic data; TRACE (psycholinguistics); Biology; Demography; History; Computer science; Sociology; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000349418,0.0002554418,0.0002606373,0.0008493293,0.001148712,0.0009825353,0.0007735356,0.0003834924,0.01036608],"category_scores_gemma":[0.002015617,0.0002085798,0.0003568498,0.00275661,0.0003864309,0.0005278846,0.0003624396,0.0004721698,0.0007876566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008615486,"about_ca_system_score_gemma":0.007909398,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9806787,"about_ca_topic_score_gemma":0.9843465,"domain_scores_codex":[0.9998473,0.00004252058,0.000006671145,0.00004611632,0.0000269107,0.00003047643],"domain_scores_gemma":[0.9994084,0.0001605384,0.00005240093,0.00009849991,0.0002367383,0.00004351169],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002133452,0.00007258725,0.1959508,0.0002788921,0.0002984529,0.0003753509,0.0008640953,0.6123406,0.002809245,0.05018386,0.06051036,0.07610238],"study_design_scores_gemma":[0.00007176361,0.00003589116,0.209896,0.0002999495,0.000124604,0.0001352195,0.0008760909,0.6598161,0.00115831,0.01734876,0.1101191,0.0001182954],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7579297,0.00206474,0.03623787,0.003114264,0.00008841367,0.0001052154,0.1593203,0.001221623,0.03991794],"genre_scores_gemma":[0.9313549,0.001129445,0.01510149,0.0002525639,0.00001555982,0.00006559727,0.04117668,0.000140088,0.01076363],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01932126,"threshold_uncertainty_score":0.06250995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01762343921009481,"score_gpt":0.2828314688507743,"score_spread":0.2652080296406795,"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."}}