{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.08494255,0.001105358,0.001218204,0.003062697,0.001146439,0.00278915,0.002748579,0.00177632,0.007699457],"category_scores_gemma":[0.3081798,0.0008991105,0.00136742,0.004289012,0.002056568,0.006526622,0.005545564,0.00199284,0.003432873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00181476,"about_ca_system_score_gemma":0.00251945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002368866,"about_ca_topic_score_gemma":0.002003279,"domain_scores_codex":[0.911804,0.07018803,0.004014075,0.005855047,0.007212233,0.0009264525],"domain_scores_gemma":[0.6900557,0.2129969,0.01435489,0.06161482,0.0197428,0.001235003],"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":[0.001813806,0.0006275763,0.08268387,0.0009160199,0.0004368913,0.0003051573,0.008947974,0.02545286,0.005957161,0.1932029,0.03515363,0.6445022],"study_design_scores_gemma":[0.001218497,0.002241449,0.09140452,0.0007178963,0.0005315791,0.001328466,0.004442757,0.36729,0.02194366,0.3533481,0.1548349,0.0006981448],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07594445,0.0002306619,0.908026,0.002085765,0.0005671047,0.002063802,0.001561272,0.002411541,0.007109385],"genre_scores_gemma":[0.3960396,0.0002196958,0.5889632,0.00087247,0.0005105298,0.006255056,0.001758028,0.000660901,0.004720611],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.08494255,"threshold_uncertainty_score":0.4492245,"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."}}