{"id":"W3113820598","doi":"10.1007/s00332-020-09661-6","title":"The Microscopic Derivation and Well-Posedness of the Stochastic Keller–Segel Equation","year":2020,"lang":"en","type":"article","venue":"Journal of Nonlinear Science","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Limit (mathematics); Diffusion; Field (mathematics); Algorithm; Computer science; Mathematics; Mathematical analysis; Physics; Thermodynamics; Pure mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001184522,0.00007020579,0.0001580983,0.00003225445,0.0002133827,0.00004110769,0.0005295881,0.00002832072,0.000007335085],"category_scores_gemma":[0.004399162,0.0000339687,0.00004648574,0.0003808226,0.0006884443,0.000125577,0.0001272088,0.0001709093,0.000002748741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002068746,"about_ca_system_score_gemma":0.0001727677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.088719e-7,"about_ca_topic_score_gemma":9.185864e-7,"domain_scores_codex":[0.9988754,0.00005966585,0.0004378838,0.00009335484,0.0004039877,0.0001297173],"domain_scores_gemma":[0.9982414,0.0007121586,0.0005487553,0.0001528961,0.0002739231,0.00007090175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002004328,0.0003896227,0.004438968,0.0005445582,0.00007497154,0.0000072393,0.009703812,0.0002743284,0.8861696,0.09226364,0.0008279006,0.005104946],"study_design_scores_gemma":[0.003194803,0.001621776,0.02624061,0.0009587409,0.00029781,0.0004355008,0.00329343,0.258433,0.3870467,0.3172683,0.0006284058,0.0005808819],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701966,0.00006520261,0.02523319,0.004105057,0.0001643857,0.000133762,0.000001218003,0.000004236558,0.0000963255],"genre_scores_gemma":[0.9866326,0.000006832869,0.01308507,0.0001619837,0.00008677002,6.046261e-7,5.832957e-8,0.000004855734,0.00002120694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4991229,"threshold_uncertainty_score":0.5266526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05101295668453239,"score_gpt":0.3075348979619357,"score_spread":0.2565219412774034,"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."}}