{"id":"W3171290486","doi":"10.1007/s13278-021-00759-7","title":"Evaluating metrics in link streams","year":2021,"lang":"en","type":"article","venue":"Social Network Analysis and Mining","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Betweenness centrality; Centrality; Computer science; Correctness; Node (physics); Theoretical computer science; Benchmark (surveying); Closeness; Mathematical proof; Algorithm; Data mining; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.007622515,0.001581858,0.001578176,0.01204876,0.0008045542,0.003787118,0.001348873,0.001638281,0.001129556],"category_scores_gemma":[0.05275583,0.0004153063,0.0007967653,0.008461666,0.0007620709,0.007231127,0.001772684,0.001133689,0.0004469178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001763463,"about_ca_system_score_gemma":0.001351375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003641806,"about_ca_topic_score_gemma":0.005556798,"domain_scores_codex":[0.992415,0.002191361,0.0007399168,0.00111078,0.003241658,0.0003012573],"domain_scores_gemma":[0.9603992,0.02725909,0.003738919,0.00248721,0.004816881,0.001298582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001031979,0.00082861,0.1225401,0.0007297268,0.0006032661,0.0003622277,0.0004978233,0.3183284,0.005701968,0.02794267,0.01106228,0.510371],"study_design_scores_gemma":[0.00001615878,0.0001937742,0.005787479,0.00004432658,0.0000630307,0.0000890399,0.0001349582,0.9626703,0.001988129,0.0273779,0.001618758,0.0000160051],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4427635,0.003421272,0.5379854,0.001295312,0.000313648,0.0005739164,0.00699481,0.00282513,0.003826961],"genre_scores_gemma":[0.861945,0.0009943016,0.1267141,0.00008802034,0.0002598322,0.0003186624,0.007622467,0.0001735791,0.001884023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9879512,"threshold_uncertainty_score":0.04031217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03565725741821606,"score_gpt":0.3474851629677249,"score_spread":0.3118279055495088,"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."}}