{"id":"W2056073610","doi":"10.1115/imece2013-63250","title":"Two New Competition Indexes on the Basis of Lotka-Volterra Competition Model","year":2013,"lang":"en","type":"article","venue":"","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Interspecific competition; Competition (biology); Tensor (intrinsic definition); Population; Equilibrium point; Stability (learning theory); Competition model; Mathematics; Mathematical economics; Econometrics; Computer science; Ecology; Economics; Microeconomics; Biology; Mathematical analysis; Pure mathematics; Demography; Machine learning","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":[0.001036896,0.0008432945,0.0008077695,0.001381369,0.000604296,0.001536808,0.001706378,0.0009299309,0.002724326],"category_scores_gemma":[0.002570254,0.0002839583,0.001098254,0.001152478,0.0009997007,0.004299604,0.001071228,0.00115235,0.0003206885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001527979,"about_ca_system_score_gemma":0.001264471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002442005,"about_ca_topic_score_gemma":0.002063742,"domain_scores_codex":[0.9990594,0.0002413375,0.00006268011,0.0001328506,0.000396052,0.00010776],"domain_scores_gemma":[0.9992034,0.0003205422,0.0001167875,0.0000420526,0.0002182666,0.00009914217],"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":[0.00008492301,0.00009515427,0.00340683,0.0002663552,0.0001143926,0.0002560024,0.0002435622,0.2347484,0.006143841,0.7256499,0.002786484,0.0262042],"study_design_scores_gemma":[0.000018774,0.00005867711,0.001050852,0.00002126543,0.00003985345,0.0001993092,0.00005413265,0.8681614,0.0005152744,0.1271264,0.002684521,0.00006962167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04921152,0.001888121,0.9267195,0.0009046716,0.0002829418,0.00008923067,0.0002033878,0.0001467756,0.02055387],"genre_scores_gemma":[0.8725893,0.002062411,0.114511,0.0002067293,0.0002854735,0.0003285889,0.0003389983,0.0000772318,0.009600129],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002724326,"threshold_uncertainty_score":0.01108634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04590013789209697,"score_gpt":0.2925014451312363,"score_spread":0.2466013072391394,"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."}}