{"id":"W2741208098","doi":"10.24963/ijcai.2017/715","title":"AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract)","year":2017,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Exploit; Speedup; Algorithm; Set (abstract data type); Range (aeronautics); Construct (python library); State (computer science); Selection (genetic algorithm); Artificial intelligence; Parallel computing","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0004204909,0.0001349135,0.0001456383,0.00006141191,0.0005462485,0.001252186,0.00188326,0.00007994239,0.0002385171],"category_scores_gemma":[0.0002266483,0.0001125118,0.00003943689,0.00006196708,0.00006250665,0.001244804,0.0001582593,0.0001853351,0.0004476074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002024325,"about_ca_system_score_gemma":0.0001043559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002427086,"about_ca_topic_score_gemma":0.00003441167,"domain_scores_codex":[0.9987308,0.00004879669,0.000220716,0.0004439196,0.0002831505,0.0002725635],"domain_scores_gemma":[0.9975582,0.00004986701,0.0001909069,0.001911689,0.0001003648,0.0001889697],"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":[0.000001916605,0.0001212035,0.0001851897,0.000007351316,0.00001310444,0.00001156704,0.0001322106,0.000003227286,0.001722366,0.203601,0.001594729,0.7926061],"study_design_scores_gemma":[0.0002249745,0.00006217653,0.349297,0.000005691633,0.000003524289,0.00001228952,0.000005314012,0.6375614,0.0005856258,0.002559971,0.009521957,0.0001600159],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004307791,0.000009234913,0.8998245,0.003982131,0.0003450621,0.0001528386,0.000007224468,0.001130925,0.0902403],"genre_scores_gemma":[0.6816,0.000002693267,0.3153877,0.0002744995,0.0001024572,0.00001095794,0.00002971271,0.000009865334,0.002582069],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7924461,"threshold_uncertainty_score":0.9997846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0219285816639395,"score_gpt":0.312509864902566,"score_spread":0.2905812832386265,"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."}}