{"id":"W2974961091","doi":"10.48550/arxiv.1803.02917","title":"Rapidly forming, slowly evolving, spatial patterns from quasi-cycle Mexican Hat coupling","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Nonlinear Dynamics and Pattern Formation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Amplitude; Coupling (piping); Physics; Statistical physics; Synchronization (alternating current); Phase synchronization; Lattice (music); Pattern formation; Phase (matter); Mathematics; Topology (electrical circuits); Quantum mechanics; Engineering; Combinatorics","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":[0.0002112447,0.0001933685,0.0001891609,0.0004142476,0.0002549631,0.0005929235,0.0003795254,0.0003956093,0.001370262],"category_scores_gemma":[0.001485819,0.0002294601,0.0002418774,0.0002250246,0.0008030962,0.0006071945,0.0004714464,0.0003784392,0.0002001249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003157899,"about_ca_system_score_gemma":0.0002192768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000482971,"about_ca_topic_score_gemma":0.0003792484,"domain_scores_codex":[0.9998716,0.00003177383,0.000006480412,0.00002542195,0.00004006657,0.00002469209],"domain_scores_gemma":[0.999563,0.0001182897,0.0001196036,0.00007808099,0.00005148892,0.00006948019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003795901,0.0001307511,0.01259471,0.000262446,0.0001084699,0.00129512,0.001131253,0.1593006,0.4749059,0.3071305,0.002733414,0.04002746],"study_design_scores_gemma":[0.00005067306,0.0001302191,0.011925,0.00001794782,0.00002626987,0.0008292845,0.0001648559,0.8449956,0.04028757,0.09857909,0.002935929,0.00005766711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8661572,0.0002199529,0.1257285,0.0002520383,0.00003955867,0.00003757572,0.00008766855,0.0002738186,0.007203647],"genre_scores_gemma":[0.9896721,0.0001013228,0.008802475,0.00003267276,0.00001140544,0.00002715119,0.00006038526,0.00002681364,0.001265686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001370262,"threshold_uncertainty_score":0.004583955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03666357265991887,"score_gpt":0.1908705883124704,"score_spread":0.1542070156525515,"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."}}