{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005833704,0.00205905,0.001948765,0.002447195,0.0006517945,0.003266052,0.001574659,0.001589997,0.002609393],"category_scores_gemma":[0.020378,0.0007860523,0.0008894628,0.002701703,0.001252227,0.003487688,0.001523281,0.00215219,0.0009655548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002079138,"about_ca_system_score_gemma":0.002612168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002274352,"about_ca_topic_score_gemma":0.002581055,"domain_scores_codex":[0.9957806,0.001648255,0.0002966603,0.0006782574,0.001219092,0.0003771317],"domain_scores_gemma":[0.9887261,0.008742039,0.0009184835,0.0004484071,0.001042639,0.0001222981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009348991,0.0001365667,0.001310054,0.0002256579,0.00006093353,0.00007108771,0.00008052881,0.8185721,0.002752726,0.01745946,0.003589062,0.1556484],"study_design_scores_gemma":[0.000009499998,0.00002785361,0.0001192681,0.00002299632,0.00001274112,0.0000275036,0.00002382866,0.9782516,0.001383193,0.01945288,0.0006627663,0.000005923384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01303905,0.0005282481,0.980819,0.0006404928,0.00004597317,0.0001349614,0.0001269442,0.0005792723,0.00408597],"genre_scores_gemma":[0.316921,0.0006385826,0.6774945,0.0004559289,0.0001358345,0.0006859215,0.0004033465,0.0003864311,0.002878496],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005833704,"threshold_uncertainty_score":0.0308519,"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."}}