{"id":"W7056804350","doi":"","title":"Guiding Expert Database Tuning with Explainable AI","year":2025,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"Thermal properties of materials","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"York University","keywords":"IBM; Workload; Expert system; Benchmark (surveying); Domain (mathematical analysis); SQL; Data manipulation language","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00006058142,0.0006803855,0.0007089201,0.001019904,0.0004565783,0.0007509384,0.00222335,0.0004035909,0.01300609],"category_scores_gemma":[0.00002126585,0.0007182747,0.0001678807,0.0007400197,0.0004496242,0.004156857,0.001925268,0.0002392563,0.001199207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000223238,"about_ca_system_score_gemma":0.0006555532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006025007,"about_ca_topic_score_gemma":0.0000209101,"domain_scores_codex":[0.9973583,0.0001797126,0.0002085409,0.001082266,0.0004065853,0.0007646365],"domain_scores_gemma":[0.9981802,0.00008935329,0.000335038,0.001014485,0.0000434568,0.0003374963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001168476,0.0001629312,0.0001707269,0.0002726277,0.0001819105,0.00201303,0.0001754819,0.00003414508,0.004421518,0.008186207,0.9828168,0.0003962053],"study_design_scores_gemma":[0.0009670191,0.0001005342,0.000003111925,0.00126565,0.00008395364,0.0000109873,0.003165384,0.00000400605,0.003937481,0.0000119914,0.9895537,0.0008961751],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002917008,0.0003771493,0.0008577546,0.0002787313,0.0004982495,0.0005176358,0.003483731,0.002082515,0.9889872],"genre_scores_gemma":[0.008980884,0.0001458587,0.002566113,0.0003041912,0.0002233173,3.102991e-7,0.0006785491,0.0003232646,0.9867775],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01180688,"threshold_uncertainty_score":0.9995785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01645789177396149,"score_gpt":0.1713219273581501,"score_spread":0.1548640355841886,"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."}}