{"id":"W2154998993","doi":"10.1177/1525822x06298588","title":"Simplifying the Personal Network Name Generator","year":2007,"lang":"en","type":"article","venue":"Field Methods","topic":"Social Capital and Networks","field":"Social Sciences","cited_by":371,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Generator (circuit theory); Respondent; Computer science; Sample (material); Interpreter; Personal network; Statistics; Mathematics; Computer network; Power (physics)","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":[],"consensus_categories":[],"category_scores_codex":[0.004582563,0.00006932698,0.0001011077,0.00001080873,0.0009467451,0.00005573513,0.0001917413,0.0001625651,0.0006493809],"category_scores_gemma":[0.0004608485,0.00005040647,0.00009798868,0.0002437284,0.0001062902,0.00005295604,0.00004374347,0.0002582446,0.00001669934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003181719,"about_ca_system_score_gemma":0.00005899245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004296748,"about_ca_topic_score_gemma":0.000549245,"domain_scores_codex":[0.9986996,0.0004306917,0.0001239144,0.0001287259,0.0001940605,0.0004230088],"domain_scores_gemma":[0.9975935,0.002130362,0.00004410219,0.00009067725,0.00004173147,0.00009966129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003250064,0.00001586911,0.003161192,0.000003802596,0.00003243144,0.000008168715,0.05183568,0.00001082964,0.0001457327,0.07412741,0.05012979,0.8204966],"study_design_scores_gemma":[0.00009856728,0.00004102265,0.002934613,0.000009412251,0.00002046846,0.000001199855,0.012658,0.0001237769,0.0004271623,0.01822481,0.9652836,0.0001773334],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.122832,0.0084216,0.4644734,0.0139498,0.007895681,0.0005073484,0.000001480363,0.0002672913,0.3816513],"genre_scores_gemma":[0.8368458,0.0003255289,0.1176874,0.01534937,0.02214248,0.00002041469,0.000001900888,0.00002294151,0.00760416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9151539,"threshold_uncertainty_score":0.7281694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0656667313736355,"score_gpt":0.4438661846357884,"score_spread":0.3781994532621529,"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."}}