{"id":"W3198151484","doi":"10.1093/notesj/gjab120","title":"George Aitken’s Genealogy of Dr John Arbuthnot","year":2021,"lang":"en","type":"article","venue":"Notes and Queries","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Biography; Expansive; George (robot); Genealogy; History; Classics; Art history","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002348632,0.0002834074,0.0002583885,0.001454936,0.003366225,0.00421907,0.0006372717,0.001429305,0.03577927],"category_scores_gemma":[0.02713625,0.0003010655,0.0001236445,0.00142436,0.004756753,0.004294559,0.001578837,0.004546021,0.01330478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003249539,"about_ca_system_score_gemma":0.004174722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03186399,"about_ca_topic_score_gemma":0.05455608,"domain_scores_codex":[0.9974784,0.0009787951,0.0001339705,0.0004396948,0.0008467688,0.0001223395],"domain_scores_gemma":[0.9922316,0.004293489,0.000444246,0.0008849036,0.001566406,0.0005793102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002650893,0.000004151018,0.000392349,0.00006360059,0.000002225663,0.0001415645,0.004553976,0.0000274008,0.0001370912,0.03963151,0.910031,0.0449886],"study_design_scores_gemma":[9.379286e-7,0.000001824162,0.0002112269,0.0001178168,6.645831e-7,0.0002209673,0.0006308457,0.00002139599,0.00008070113,0.003821929,0.9948862,0.000005476984],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.006178765,0.07412195,0.01428939,0.5935406,0.03079029,0.0001149752,0.001586798,0.0006812583,0.2786959],"genre_scores_gemma":[0.1184264,0.04713751,0.01709216,0.1028634,0.008432562,0.0002007797,0.0009007316,0.001578814,0.7033677],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03577927,"threshold_uncertainty_score":0.1196936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555939475541807,"score_gpt":0.3120825675261561,"score_spread":0.286523172770738,"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."}}