{"id":"W4396212849","doi":"10.61091/jcmcc119-09","title":"Predictive Modelling of Students’ University English Language Performance by Classification with Gaussian Process Models","year":2024,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Advanced Data Processing Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Process (computing); Gaussian process; Natural language processing; Mathematics education; Artificial intelligence; Gaussian; Linguistics; Psychology; Programming language; Physics; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004884297,0.0001916646,0.0003839871,0.0001631546,0.00008540617,0.000109289,0.0003461564,0.000103013,7.256698e-7],"category_scores_gemma":[0.00002706346,0.0001704338,0.0000449826,0.0003158354,0.00006653594,0.00071292,0.00006175979,0.000404506,1.452176e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001070983,"about_ca_system_score_gemma":0.0000696537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001389249,"about_ca_topic_score_gemma":4.326932e-8,"domain_scores_codex":[0.9986764,0.00002355631,0.0004773216,0.0001452234,0.0005050728,0.0001724319],"domain_scores_gemma":[0.9990113,0.000145188,0.0002793392,0.000139965,0.000340498,0.00008375148],"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":[0.0008418825,0.001529904,0.0005011884,0.01177403,0.001266345,0.0001100805,0.07140265,0.3188517,0.004209364,0.5799177,0.0007747163,0.008820426],"study_design_scores_gemma":[0.001060255,0.0004515722,0.000004502544,0.001691826,0.00009654831,0.00001986655,0.002391336,0.9395093,0.004151012,0.05031414,0.0000852185,0.0002244565],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6436942,0.0004575839,0.3539421,0.00000413128,0.001230652,0.0001269335,0.000009105609,0.000151733,0.0003835981],"genre_scores_gemma":[0.99106,0.0001909683,0.00845816,7.8954e-7,0.0002445168,7.431946e-7,0.000004098622,0.00003845484,0.000002238692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6206576,"threshold_uncertainty_score":0.6950087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01241202403988061,"score_gpt":0.2382875136785237,"score_spread":0.2258754896386431,"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."}}