{"id":"W2498775271","doi":"","title":"Synchronization, TIGoRS, and Information Flow in Complex Systems: Dispositional Cellular Automata.","year":2016,"lang":"en","type":"article","venue":"PubMed","topic":"Cellular Automata and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Synchronization (alternating current); Cellular automaton; Context (archaeology); Computer science; Automaton; Salient; Information flow; Complex system; Argument (complex analysis); Phenomenon; Cognitive science; Theoretical computer science; Artificial intelligence; Physics; Biology; Psychology; Linguistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006095463,0.0006028512,0.0005328506,0.001298524,0.0006664349,0.001841886,0.0006478472,0.001283401,0.001964167],"category_scores_gemma":[0.002798996,0.0002408814,0.000585049,0.001609931,0.003593512,0.002813775,0.001509521,0.001783806,0.0003764383],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001258098,"about_ca_system_score_gemma":0.0005679308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001328355,"about_ca_topic_score_gemma":0.001215432,"domain_scores_codex":[0.9995918,0.0001351894,0.00003395546,0.000106297,0.00009807028,0.00003472233],"domain_scores_gemma":[0.9992226,0.0004021405,0.0001348512,0.00008188272,0.00008152508,0.00007698951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001441757,0.000007706468,0.0004031569,0.00009252237,0.0000147401,0.0000925666,0.000210999,0.01391547,0.001025354,0.9673238,0.002090539,0.01480864],"study_design_scores_gemma":[0.000006483812,0.00004108151,0.0006297342,0.00006614529,0.00001738562,0.0002612549,0.0001119153,0.08626455,0.000465658,0.8877934,0.0243086,0.00003374912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05476125,0.06646535,0.8016366,0.006823986,0.00172986,0.0001406242,0.0005633822,0.0006307439,0.06724836],"genre_scores_gemma":[0.882094,0.02058106,0.08620802,0.0008021684,0.001257947,0.000241147,0.0002993822,0.00009087414,0.008425498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001964167,"threshold_uncertainty_score":0.009128213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009002847387088408,"score_gpt":0.1777524463389916,"score_spread":0.1687495989519033,"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."}}