{"id":"W1595035399","doi":"10.1007/11863649_1","title":"Automated Social Network Analysis for Collaborative Work","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Collaborative software; Work (physics); Computer-supported cooperative work; Human–computer interaction; Social network analysis; Software; World Wide Web; Social network (sociolinguistics); Collaborative network; Data science; Software engineering; Knowledge management; Engineering; Social media","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004936996,0.0004837787,0.0009178405,0.000626809,0.0004755743,0.0003089467,0.0008450414,0.0001912395,0.00008656958],"category_scores_gemma":[0.000004880698,0.0004701507,0.0004859883,0.003067267,0.0004487774,0.0001126368,0.0003001797,0.0003901532,0.00000487081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001781247,"about_ca_system_score_gemma":0.0002590702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004440836,"about_ca_topic_score_gemma":0.0001205361,"domain_scores_codex":[0.9973724,0.00003500868,0.0005303662,0.0009882048,0.0004487039,0.0006253521],"domain_scores_gemma":[0.9981769,0.000396253,0.0004496496,0.0004958431,0.0004124292,0.00006894372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002327693,0.000048674,0.005626097,0.00001014593,0.0007873138,0.000004341157,0.0002370066,0.8123752,0.00000484994,0.02425903,0.007661417,0.1489626],"study_design_scores_gemma":[0.0002947377,0.00007428486,0.00165571,0.000121706,0.0007299557,2.539655e-7,3.741829e-7,0.693095,0.00008072999,0.2917079,0.01118116,0.001058233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00008180073,0.0001276013,0.9923306,0.0001514798,0.0002169173,0.0005182648,0.00004311206,0.0002875977,0.006242684],"genre_scores_gemma":[0.7480239,0.000001868922,0.2461852,0.0002303244,0.004099431,0.00007745795,0.0003852372,0.00006553946,0.0009309393],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7479421,"threshold_uncertainty_score":0.999775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01287660380328165,"score_gpt":0.2679299655267166,"score_spread":0.2550533617234349,"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."}}