{"id":"W2463015236","doi":"10.5153/sro.3827","title":"The Biographical Network Method","year":2016,"lang":"en","type":"article","venue":"Sociological Research Online","topic":"Social and Cultural Dynamics","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Dynamism; Relation (database); Sociology; Cosmopolitanism; Social network analysis; Visualization; Computer science; Epistemology; Social science; Artificial intelligence; Social capital; Politics; Law; Data mining; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.00798216,0.00008171461,0.0001365431,0.0000195407,0.003513702,0.00007634234,0.0006657131,0.0003076512,0.0003058247],"category_scores_gemma":[0.007380038,0.00003086477,0.0001667583,0.0007392535,0.003785772,0.00006113623,0.0001878909,0.0005377978,0.0001103463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001164724,"about_ca_system_score_gemma":0.000149788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003046585,"about_ca_topic_score_gemma":0.00196472,"domain_scores_codex":[0.9944494,0.003278329,0.0001733531,0.0002526358,0.000806867,0.001039388],"domain_scores_gemma":[0.9912695,0.007929941,0.00003367833,0.000153048,0.0003686397,0.0002451953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003449416,0.00005124305,0.002947737,5.605906e-7,0.00002021763,0.000003932311,0.0004923269,4.198207e-7,0.0001547735,0.8030417,0.01443132,0.1788213],"study_design_scores_gemma":[0.00009984253,0.00008203113,0.0116994,0.000009130981,0.000002125839,1.725446e-7,0.003114905,0.00001184627,9.272392e-7,0.5019515,0.4829578,0.00007039542],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2724066,0.00332471,0.00305331,0.6691981,0.001123634,0.001162822,0.00008831738,0.0005514157,0.04909112],"genre_scores_gemma":[0.9419389,0.02364351,0.004881172,0.001029643,0.007422303,0.000102083,0.00001895118,0.00001785314,0.02094553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6695324,"threshold_uncertainty_score":0.9989253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2722365022771613,"score_gpt":0.5665851940040558,"score_spread":0.2943486917268945,"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."}}