{"id":"W4321489718","doi":"10.1080/01605682.2023.2181715","title":"Explainable prediction of Qcodes for NOTAMs using column generation","year":2023,"lang":"en","type":"article","venue":"Journal of the Operational Research Society","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; Polytechnique Montréal","funders":"","keywords":"Computer science; Artificial intelligence; Machine learning; Column (typography); Interpretability; Operations research; Algorithm; Mathematics","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":[0.003873687,0.00004934944,0.0001032834,0.00005965411,0.0006443689,0.0001800825,0.0005460403,0.00005162426,0.000006168837],"category_scores_gemma":[0.0003846831,0.00003211649,0.0001944808,0.0006429526,0.00007723735,0.0005660419,0.0001612132,0.0001922833,0.000001472898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000144089,"about_ca_system_score_gemma":0.0005215981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001416527,"about_ca_topic_score_gemma":0.000002130985,"domain_scores_codex":[0.9982914,0.0001525928,0.0003055171,0.000107083,0.0009486806,0.0001946663],"domain_scores_gemma":[0.9981525,0.0002568387,0.0001306745,0.0001693356,0.001244804,0.00004585905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004873178,0.0002327098,0.001579058,0.0001038855,0.0001942487,0.000003388224,0.004886528,0.2587201,0.3468021,0.04001238,0.3420396,0.005377316],"study_design_scores_gemma":[0.0003302825,0.0001696166,0.002071696,0.00003238666,0.000004400903,0.00001307557,0.0002511852,0.98483,0.005735841,0.003697455,0.00282904,0.00003502178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5704141,0.0002952799,0.4163258,0.01077237,0.00118924,0.0006897851,0.00004538695,0.00002111232,0.0002468729],"genre_scores_gemma":[0.8995854,0.0001893373,0.09846418,0.0001646846,0.0009161285,0.00001766729,0.000005746499,0.000008499575,0.0006483094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7261099,"threshold_uncertainty_score":0.4956029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3138019965474357,"score_gpt":0.4117655621727654,"score_spread":0.09796356562532971,"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."}}