{"id":"W2792828486","doi":"10.1017/nws.2017.19","title":"Temporal evolution of the degree distribution of alters in growing networks","year":2018,"lang":"en","type":"article","venue":"Network Science","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; James S. McDonnell Foundation","keywords":"Observability; Degree distribution; Preferential attachment; Computer science; Degree (music); Statistical physics; Network topology; Complex network; Synchronization (alternating current); Network dynamics; Evolving networks; Random graph; Interdependent networks; Theoretical computer science; Mathematics; Applied mathematics; Physics; Graph; Discrete 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000886209,0.00008324922,0.0001587495,0.00004700551,0.0001742733,0.0000148285,0.0005364579,0.00002183599,0.00002219556],"category_scores_gemma":[0.00001119917,0.00006420622,0.00008567503,0.002379386,0.0008528266,0.0002174156,0.0002091257,0.0001073608,6.670207e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000857677,"about_ca_system_score_gemma":0.00009827191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006692659,"about_ca_topic_score_gemma":0.0001152603,"domain_scores_codex":[0.998856,0.00005903985,0.0003067178,0.0002067654,0.0002683962,0.0003030571],"domain_scores_gemma":[0.9991961,0.00003992856,0.0002352859,0.0003563632,0.000140273,0.00003206845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008813614,0.00004225733,0.9171911,0.000002018624,0.000007244038,5.474574e-8,0.00004640538,0.02408715,0.0005326316,0.0470767,0.0009990421,0.01000661],"study_design_scores_gemma":[0.0001613362,0.00005974444,0.644463,0.0001654141,0.00002125873,2.968376e-7,0.00007602591,0.3346076,0.002339336,0.0175493,0.0004160218,0.0001406925],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8049135,0.00005671093,0.1926637,0.00005082567,0.0002088388,0.0001458,0.000002892418,0.00001474706,0.001943023],"genre_scores_gemma":[0.9988667,7.812838e-7,0.0007341887,0.00001078231,0.0003639479,0.000005103643,0.000004519017,0.000003799938,0.00001016834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3105204,"threshold_uncertainty_score":0.3142275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01743110528949425,"score_gpt":0.2574856976997779,"score_spread":0.2400545924102837,"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."}}