{"id":"W4408830429","doi":"10.3390/math13071059","title":"Optimizing Accuracy, Recall, Specificity, and Precision Using ILP","year":2025,"lang":"en","type":"article","venue":"Mathematics","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Recall; Computer science; Precision and recall; Artificial intelligence; Machine learning; Psychology; Cognitive psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003797444,0.0001057861,0.0001557299,0.0001337656,0.0001161569,0.0002772424,0.0006589197,0.00006320613,0.000005871119],"category_scores_gemma":[0.0002463382,0.00009684212,0.00002316588,0.0003373688,0.00004027919,0.0004411661,0.0005988836,0.000101385,0.000009535609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005332604,"about_ca_system_score_gemma":0.00003776269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002141406,"about_ca_topic_score_gemma":6.038466e-7,"domain_scores_codex":[0.9991149,0.00002874562,0.000283149,0.0002584961,0.0001659115,0.0001488017],"domain_scores_gemma":[0.9987058,0.0003161165,0.0001222732,0.0007535753,0.00006890835,0.00003332019],"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":[0.000003591889,0.0001936894,0.000101738,0.0002559407,0.0000220525,0.000005819114,0.001792634,0.00006680573,0.03900624,0.8517173,0.005392998,0.1014412],"study_design_scores_gemma":[0.0001954936,0.00002217739,0.0002128945,0.0004146697,0.00001347029,0.00002271431,0.0001191811,0.7237224,0.07297717,0.1948724,0.007167315,0.0002601455],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007752326,0.00007902413,0.9876275,0.0003829003,0.0001023415,0.0001955217,0.00000251853,0.0002792807,0.003578551],"genre_scores_gemma":[0.03581821,0.00006782108,0.9637156,0.0001208854,0.00001421012,0.000007950782,0.000001601534,0.000006810103,0.0002468918],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7236556,"threshold_uncertainty_score":0.3949107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04936020873309961,"score_gpt":0.3233243585947993,"score_spread":0.2739641498616997,"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."}}