{"id":"W4409921629","doi":"10.1016/j.physd.2025.134682","title":"Biological aggregations from spatial memory and nonlocal advection","year":2025,"lang":"en","type":"article","venue":"Physica D Nonlinear Phenomena","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Engineering and Physical Sciences Research Council; China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; National Science Foundation","keywords":"Advection; Statistical physics; Physics; Mathematics; Quantum mechanics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003671684,0.0003974029,0.0003480721,0.0004588009,0.0004974711,0.001182306,0.0007111584,0.0009455754,0.0009150757],"category_scores_gemma":[0.001101268,0.0001925151,0.0006294702,0.0002912839,0.001160937,0.001170584,0.001875445,0.0004973664,0.0001200879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005254714,"about_ca_system_score_gemma":0.0003488688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002264498,"about_ca_topic_score_gemma":0.001357622,"domain_scores_codex":[0.9998654,0.00003528945,0.000007934891,0.0000283166,0.00003391006,0.00002918244],"domain_scores_gemma":[0.9995403,0.0001531489,0.0001600795,0.00006119694,0.00004310406,0.00004221685],"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":[0.00008092196,0.000102356,0.005279997,0.000130977,0.00007158917,0.001700891,0.0008934351,0.7847312,0.03711641,0.1563748,0.0004355507,0.01308192],"study_design_scores_gemma":[0.00001662579,0.00005056361,0.00103237,0.00000837166,0.00001939765,0.0001682176,0.0001048496,0.9701361,0.002592769,0.02537135,0.0004810783,0.00001818286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7961075,0.0003519612,0.1903147,0.0005512853,0.00003439056,0.00004050675,0.00002780728,0.0001235057,0.01244828],"genre_scores_gemma":[0.9923589,0.0000880166,0.005766201,0.00003367384,0.00001064292,0.00001615266,0.000007992794,0.000006732078,0.001711811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002264498,"threshold_uncertainty_score":0.004502654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02872787458496663,"score_gpt":0.2949342525138712,"score_spread":0.2662063779289046,"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."}}