{"id":"W2091203323","doi":"10.1007/s10462-009-9144-3","title":"A query-based approach for test selection in diagnosis","year":2008,"lang":"en","type":"article","venue":"Artificial Intelligence Review","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Selection (genetic algorithm); Query optimization; Test (biology); Test case; Entropy (arrow of time); Computation; Minification; Machine learning; Data mining; Mathematical optimization; 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":[0.0008962445,0.0001617401,0.0002995462,0.000121279,0.0002000532,0.00004728458,0.0004814916,0.00006558139,0.00001916935],"category_scores_gemma":[0.0006647383,0.0001508437,0.0001222239,0.001067868,0.00004373032,0.0002294317,0.00003297257,0.0001674459,0.0000594758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005993829,"about_ca_system_score_gemma":0.0001709616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009576124,"about_ca_topic_score_gemma":0.00002849189,"domain_scores_codex":[0.9984173,0.0001029862,0.0005139497,0.0004426617,0.0001777099,0.0003454139],"domain_scores_gemma":[0.9987102,0.0007268287,0.0001297156,0.0002485409,0.0001083741,0.00007632659],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001307779,0.0008801679,0.02097748,0.002766337,0.00001495568,0.00002354405,0.0005615492,0.01554331,0.0001849125,0.02781721,0.004795956,0.9264215],"study_design_scores_gemma":[0.00005613535,0.0003949013,0.0002556127,0.003026813,0.00002686875,0.00004252679,0.00001621827,0.956065,0.01348955,0.005128449,0.02087234,0.0006255988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002790009,0.01285755,0.9844674,0.001230518,0.00006936562,0.000717568,0.000003189025,0.000126421,0.0002489124],"genre_scores_gemma":[0.5906816,0.01702115,0.3867556,0.003533851,0.0001733896,0.001703842,0.00002904333,0.00003235667,0.00006919631],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9405217,"threshold_uncertainty_score":0.6151228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1201347608078735,"score_gpt":0.3236326353724061,"score_spread":0.2034978745645326,"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."}}