{"id":"W2039736135","doi":"10.1142/s012918311550103x","title":"Extracting principal parameters of complex networks","year":2015,"lang":"en","type":"article","venue":"International Journal of Modern Physics C","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre de Recherches Mathématiques","keywords":"Eigenvalues and eigenvectors; Resolvent; Computer science; Statistical physics; Complex network; Sequence (biology); Matrix (chemical analysis); Principal (computer security); Principal component analysis; Diffusion; Mathematics; Algorithm; Artificial intelligence; Physics; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003324509,0.0001224198,0.0002845009,0.00007943736,0.00002036585,0.00004567903,0.0005180081,0.00002241454,0.00003686844],"category_scores_gemma":[0.0000146941,0.0001150562,0.000268931,0.00009626133,0.0000497684,0.0002469406,0.0001099365,0.0002381675,0.000001858811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005751758,"about_ca_system_score_gemma":0.00007867642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004555836,"about_ca_topic_score_gemma":0.000001038516,"domain_scores_codex":[0.9985722,0.00005276409,0.0005708439,0.0001045869,0.0005609544,0.0001386379],"domain_scores_gemma":[0.9977965,0.0001093697,0.0009649564,0.0001412348,0.0008915046,0.00009637058],"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":[0.0002097768,0.0006528205,0.07547861,0.000003756688,0.001595483,0.00001675674,0.0007831014,0.3708096,0.002602963,0.01993631,0.002333974,0.5255768],"study_design_scores_gemma":[0.001396223,0.0001482607,0.002068382,0.0001316545,0.0001527362,0.00002257538,0.0002246723,0.7600721,0.004768821,0.2291962,0.001509319,0.0003090857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.239027,0.00004351494,0.7574847,0.00009029435,0.0002496851,0.00004228555,0.000006946673,0.00001026086,0.003045324],"genre_scores_gemma":[0.9837328,0.000002681305,0.01520089,0.0000319635,0.0009700441,0.000001508158,0.00001583967,0.00001534665,0.00002892521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7447059,"threshold_uncertainty_score":0.4691857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0697471680995871,"score_gpt":0.3304411947271408,"score_spread":0.2606940266275537,"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."}}