{"id":"W4407832170","doi":"10.1109/icdm59182.2024.00038","title":"A Learned Approach to Index Algorithm Selection","year":2024,"lang":"en","type":"article","venue":"","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Selection (genetic algorithm); Index (typography); Algorithm; Selection algorithm; Algorithm design; Artificial intelligence","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":[0.0002042583,0.00007223588,0.00008365083,0.00009351916,0.00004693513,0.0003294994,0.0003043002,0.00004303183,0.000004999852],"category_scores_gemma":[0.000006429389,0.00005331175,0.00003992922,0.0006218029,0.000005075181,0.0002077348,0.00007684673,0.00008323981,0.0003998826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003687575,"about_ca_system_score_gemma":0.00004514986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001204672,"about_ca_topic_score_gemma":0.000003034135,"domain_scores_codex":[0.9991783,0.00003199482,0.000099077,0.0003322126,0.0001856185,0.000172759],"domain_scores_gemma":[0.9997085,0.0000200293,0.000007340952,0.0001615946,0.00002823742,0.00007424794],"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":[0.000001482534,0.00003047158,0.0000379015,0.00001484708,0.00002072966,0.000004847769,0.0003756847,0.0003898414,0.0001968212,0.406277,0.009762957,0.5828875],"study_design_scores_gemma":[0.00007759457,0.00005631216,0.0002182499,0.000006500909,0.000001616761,0.00003840789,0.0000298653,0.9661888,0.00004387236,0.008013901,0.02522024,0.0001046364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00005971126,0.0001003796,0.7810869,0.0007068169,0.0003059168,0.0001148991,1.569672e-7,0.0005152011,0.2171101],"genre_scores_gemma":[0.9038287,0.000001466968,0.08086118,0.0005369728,0.0002218773,0.00005837632,5.065141e-7,0.000006059093,0.0144849],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.965799,"threshold_uncertainty_score":0.5139815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01693024910446635,"score_gpt":0.2367513801846861,"score_spread":0.2198211310802197,"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."}}