{"id":"W3047331065","doi":"10.1080/14636778.2020.1799343","title":"The consumer representation of DNA ancestry testing on YouTube","year":2020,"lang":"en","type":"article","venue":"New Genetics and Society","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Alberta","funders":"Canadian Institutes of Health Research; Genome Alberta; Genome Canada","keywords":"Genetic genealogy; Ethnic group; Race (biology); Representation (politics); Promotion (chess); Identity (music); Social media; Phrase; Psychology; Sociology; Anthropology; Gender studies; Computer science; World Wide Web; Political science; Demography; Law; Politics; Aesthetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001397934,0.0002240871,0.0001929558,0.001892119,0.0009666028,0.00178491,0.0002293597,0.0005566032,0.00617158],"category_scores_gemma":[0.009594393,0.0001125779,0.0001338519,0.001383341,0.000520998,0.002111304,0.001295682,0.0004999812,0.0007686071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009920644,"about_ca_system_score_gemma":0.0004079778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02007168,"about_ca_topic_score_gemma":0.02657993,"domain_scores_codex":[0.9986902,0.0006090456,0.00005770545,0.0001185458,0.0003929397,0.0001314997],"domain_scores_gemma":[0.9932529,0.003913241,0.0009484325,0.0002425945,0.001352053,0.0002907723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.001061441,0.00016281,0.5415515,0.001238417,0.0001358923,0.002124988,0.1908138,0.0003764195,0.00952228,0.005600823,0.05574905,0.1916626],"study_design_scores_gemma":[0.00003921584,0.0002532478,0.5887765,0.0008737604,0.0001076082,0.001697145,0.2497732,0.004915233,0.002807294,0.001884567,0.1487181,0.0001540073],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9539512,0.0007429544,0.0007016895,0.002208345,0.0000908447,0.00007557522,0.003822008,0.00006716116,0.03834019],"genre_scores_gemma":[0.9894289,0.0007275569,0.0007077939,0.000643318,0.00008616546,0.00008991033,0.001987698,0.00005916285,0.006269496],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02007168,"threshold_uncertainty_score":0.03990972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03842493702971653,"score_gpt":0.3211931823059316,"score_spread":0.282768245276215,"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."}}