{"id":"W2809195697","doi":"10.1016/j.ins.2018.06.051","title":"Extension of neighbor-based link prediction methods for directed, weighted and temporal social networks","year":2018,"lang":"en","type":"article","venue":"Information Sciences","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Extension (predicate logic); Link (geometry); Computer science; Artificial intelligence; Social network analysis; Pattern recognition (psychology); Data mining; Mathematics; Social media; Computer network","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":[0.0008181179,0.00007043163,0.0001307491,0.0001315009,0.0003400336,0.00007243676,0.0001010824,0.0000331233,0.0000471042],"category_scores_gemma":[0.00001317144,0.00005713727,0.00005429116,0.0004303083,0.0002725695,0.0005768675,0.00002832371,0.0000396877,7.933083e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007471884,"about_ca_system_score_gemma":0.00004110156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000753505,"about_ca_topic_score_gemma":0.000002836666,"domain_scores_codex":[0.999306,0.00004750449,0.0003097421,0.00009515488,0.0001224787,0.0001191486],"domain_scores_gemma":[0.9992411,0.0001145959,0.0002642939,0.00007406012,0.0002804656,0.00002555738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003628176,0.00002001321,0.01895509,0.000009719195,0.00002270047,4.924352e-9,0.0004806327,0.0001983894,0.0003317646,0.01180978,0.002142468,0.9659932],"study_design_scores_gemma":[0.0001901194,0.0001137692,0.006751945,0.00001250419,0.00001892879,8.36118e-8,0.0000977201,0.9751695,0.002225423,0.006067072,0.009283318,0.00006966259],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02275841,0.00001316029,0.9745495,0.0001527832,0.00008955248,0.0001815863,0.00001423457,0.00007096951,0.002169773],"genre_scores_gemma":[0.8945737,8.244451e-7,0.1050098,0.0000514361,0.0002873261,0.00001903821,0.00004946476,0.000001937918,0.000006456458],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9749711,"threshold_uncertainty_score":0.2615298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02830214709320063,"score_gpt":0.3576625848827984,"score_spread":0.3293604377895978,"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."}}