{"id":"W4240002048","doi":"10.1109/asonam.2014.6921602","title":"A semantic model for academic social network analysis","year":2014,"lang":"en","type":"article","venue":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Social network (sociolinguistics); Construct (python library); Data science; Social network analysis; Foundation (evidence); Semantic data model; Artificial intelligence; Knowledge management; World Wide Web; Social media; Political science; Programming language","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":[0.001140654,0.0004680517,0.001213442,0.0005526929,0.0005564049,0.0001971323,0.0008703112,0.0001988264,0.0003701787],"category_scores_gemma":[0.00003531,0.000476355,0.000893696,0.001344902,0.0001975185,0.0003155474,0.0001920795,0.0005234766,0.000006834274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008681993,"about_ca_system_score_gemma":0.00004584517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009203118,"about_ca_topic_score_gemma":0.0007268874,"domain_scores_codex":[0.9968091,0.000207142,0.0008778656,0.0009188408,0.0004908328,0.0006962548],"domain_scores_gemma":[0.9979556,0.0004828172,0.0007520192,0.0003563886,0.0003293348,0.0001239026],"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":[0.000161272,0.0001261331,0.1487622,0.00001138237,0.004537992,8.937822e-7,0.0005562792,0.5909481,0.00001393718,0.1919147,0.01241947,0.0505476],"study_design_scores_gemma":[0.0004658142,0.00003686929,0.005051704,0.00003274844,0.002196174,1.537585e-7,0.0001758691,0.948322,0.000002612267,0.04057634,0.00265664,0.0004830959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03684265,0.000272123,0.9560545,0.0006357604,0.0002647879,0.0002650307,0.00007062806,0.00007797631,0.00551653],"genre_scores_gemma":[0.9893814,0.0004871746,0.005762341,0.0002570114,0.00279266,0.0001796747,0.000448001,0.00003706764,0.0006547144],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9525387,"threshold_uncertainty_score":0.9997688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02853513080662997,"score_gpt":0.3484171722931093,"score_spread":0.3198820414864794,"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."}}