{"id":"W2461634661","doi":"","title":"Nonlinear non-Markovian model of subdiffusive transport with chemotaxis","year":2015,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Nonlinear system; Statistical physics; Markov process; Chemotaxis; Mathematics; Physics; Applied mathematics; Computer science; Statistics; Chemistry","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":[0.0004865176,0.000570727,0.0008114321,0.000611435,0.0007846828,0.001100001,0.00142507,0.001550612,0.0022261],"category_scores_gemma":[0.0010589,0.000382079,0.0009418646,0.000495535,0.00146577,0.001625055,0.0009307567,0.0009590777,0.0002261584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001548724,"about_ca_system_score_gemma":0.001051209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007884707,"about_ca_topic_score_gemma":0.003929983,"domain_scores_codex":[0.9997634,0.0000516466,0.00001104926,0.00004861424,0.00006220739,0.00006297849],"domain_scores_gemma":[0.9996338,0.0001314825,0.00008233009,0.00003014183,0.00006124721,0.0000610082],"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":[0.0001176729,0.0001059769,0.001904496,0.0001210324,0.0000439538,0.0006110386,0.000380067,0.4473992,0.01762839,0.5264914,0.001158158,0.00403852],"study_design_scores_gemma":[0.0000172901,0.00001708412,0.0001769906,0.000004030471,0.000007860206,0.00004904423,0.00001894479,0.9737004,0.0004550757,0.02520039,0.0003422886,0.00001063544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4415348,0.001292293,0.5240732,0.002772873,0.000269157,0.0001253005,0.0003266551,0.0002440857,0.02936147],"genre_scores_gemma":[0.9678559,0.0004568551,0.009799371,0.0001753578,0.00008986048,0.0001178012,0.00007549898,0.00002801784,0.02140138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007884707,"threshold_uncertainty_score":0.01567763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1039342481617657,"score_gpt":0.2017282363704798,"score_spread":0.09779398820871414,"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."}}