{"id":"W6976580532","doi":"10.60692/3bn48-p9x26","title":"Evaluating the effect of aging on interference resolution with time-varying complex networks analysis","year":2015,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Interference (communication); Synchronization (alternating current); Complex network; Task (project management); Magnetoencephalography; Topology (electrical circuits); Network topology; Network analysis","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":[0.0009827971,0.0001157544,0.0001895005,0.0001929988,0.0001534906,0.0001996432,0.0003926249,0.00002431682,0.000001739112],"category_scores_gemma":[0.00001300908,0.00007040711,0.00006525308,0.001052199,0.00002474431,0.0004067227,0.0001048785,0.00007972454,0.0000797133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007069201,"about_ca_system_score_gemma":0.00003078255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001082635,"about_ca_topic_score_gemma":1.150723e-7,"domain_scores_codex":[0.9987791,0.0001889689,0.0003588736,0.0001393558,0.0004051016,0.000128578],"domain_scores_gemma":[0.9987419,0.00008955829,0.0003831899,0.0004711057,0.0002611736,0.00005305977],"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":[0.00004065738,0.000001105554,0.008047965,0.00002846005,0.0001045758,1.446634e-7,0.009709794,0.9768813,0.000001797495,0.002374784,0.00003247043,0.002776923],"study_design_scores_gemma":[0.0003488387,0.0002464461,0.01032263,0.00006026889,0.00005988089,0.000003861117,0.0001397593,0.9886526,0.00007095623,0.000008304952,0.000006312845,0.00008012295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1426268,0.000001375576,0.855429,0.00006897316,0.00004278197,0.0002513937,0.000005452419,0.00008340828,0.00149083],"genre_scores_gemma":[0.9968514,9.549522e-9,0.002982151,0.00005235372,0.00003156128,0.00004490056,0.00002243593,0.000003198128,0.00001199335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8542246,"threshold_uncertainty_score":0.2871119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07310370894183002,"score_gpt":0.2900308614439163,"score_spread":0.2169271525020863,"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."}}