{"id":"W1994538318","doi":"10.1007/s00285-014-0842-3","title":"Symmetries and pattern formation in hyperbolic versus parabolic models of self-organised aggregation","year":2014,"lang":"en","type":"article","venue":"Journal of Mathematical Biology","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"Engineering and Physical Sciences Research Council","keywords":"Limit (mathematics); Hopf bifurcation; Bifurcation; Mathematics; Symmetry (geometry); Homogeneous space; Stability (learning theory); Pattern formation; Type (biology); Parabolic partial differential equation; Statistical physics; Class (philosophy); Mathematical analysis; Physics; Geometry; Computer science; Ecology; Partial differential equation; Biology; Nonlinear system","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":[0.001527163,0.0002065476,0.0009257057,0.0003392839,0.0000317248,0.00001347684,0.0002492013,0.0002390559,0.00004653794],"category_scores_gemma":[0.00407195,0.0001468611,0.0001116662,0.0002267223,0.000191648,0.0002185174,0.00008061405,0.0002768974,0.00001107822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004773483,"about_ca_system_score_gemma":0.00002746513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001762602,"about_ca_topic_score_gemma":0.000003600103,"domain_scores_codex":[0.9976243,0.0003516255,0.001387642,0.0001507083,0.0002077986,0.0002778702],"domain_scores_gemma":[0.995205,0.003326662,0.0008875586,0.0002315625,0.0002378731,0.0001113563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001899285,0.0005867943,0.0006578355,0.001083969,0.0001130626,0.000007009693,0.001983833,0.000004058633,0.004454256,0.9845344,0.00009953373,0.006285261],"study_design_scores_gemma":[0.0022523,0.0006964705,0.000221756,0.0002129445,0.00009704543,0.0002219434,0.0001952478,0.009053431,0.008153403,0.978709,0.00002994002,0.0001565011],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9087654,0.0001183687,0.08887356,0.0004258388,0.00009500912,0.000215239,0.000004008989,0.00002506722,0.001477521],"genre_scores_gemma":[0.9732857,0.00007559769,0.02647699,0.00006055681,0.0000695822,0.000006236978,0.00000167041,0.00001838775,0.000005281193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06452031,"threshold_uncertainty_score":0.5988824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03818179001795379,"score_gpt":0.2916159389467409,"score_spread":0.2534341489287871,"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."}}