{"id":"W4408324204","doi":"10.21307/connections-2019.035","title":"Fractals Beyond Hierarchy—Analyzing the Temporal Patterns of Contact Networks in a French Public Sector Organization","year":2024,"lang":"en","type":"article","venue":"Connections","topic":"Complex Systems and Time Series Analysis","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Noise (video); Fractal; White noise; Computer science; Hierarchy; Chaotic; Brownian noise; Statistical physics; Artificial intelligence; Mathematics; Physics; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003625042,0.0001005241,0.000290858,0.0004084876,0.0001417007,0.0001967594,0.0001462418,0.00006347457,0.002983137],"category_scores_gemma":[0.0001278027,0.00009100021,0.0001208809,0.001445037,0.0000204576,0.0002344664,0.00004708838,0.0001659232,0.00004890389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009620887,"about_ca_system_score_gemma":0.00002843172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005136628,"about_ca_topic_score_gemma":0.003833406,"domain_scores_codex":[0.9989502,0.00002928147,0.0005609118,0.0002565534,0.00002718669,0.0001758396],"domain_scores_gemma":[0.9993151,0.0001677476,0.0001623328,0.0002583174,0.00005746914,0.00003905857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[9.368421e-7,0.00004109479,0.7512394,0.00003724096,0.0002117533,0.000003103747,0.0006281014,0.0007622408,0.00002698929,0.2457552,0.0006653328,0.0006286244],"study_design_scores_gemma":[0.0005502427,0.000123857,0.6402684,0.0001547028,0.00007417288,0.00002384391,0.001109755,0.2035814,0.00003564764,0.01750352,0.1359787,0.0005956891],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8583636,0.007855395,0.1246536,0.002823273,0.001067923,0.0003140809,0.0002258022,0.00009434624,0.004601974],"genre_scores_gemma":[0.9989392,0.00009789188,0.00002015329,0.00003466042,0.0001664656,0.00001849593,0.00005801543,0.00002034377,0.0006447497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2282517,"threshold_uncertainty_score":0.9979283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02471125974323003,"score_gpt":0.2119595718624767,"score_spread":0.1872483121192466,"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."}}