{"id":"W1543201103","doi":"10.1007/978-3-642-13800-3_30","title":"Time-Bounded Sequential Parameter Optimization","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Mathematical optimization; Bounded function; Overhead (engineering); Focus (optics); Optimization problem; Discrete 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001444512,0.002614325,0.001927724,0.0005548585,0.0005141986,0.001104903,0.001557069,0.001210541,0.01054058],"category_scores_gemma":[0.005654774,0.0008154138,0.0008200251,0.001298786,0.0009983971,0.001559381,0.002140051,0.001999545,0.00206243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007695361,"about_ca_system_score_gemma":0.001085621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002183346,"about_ca_topic_score_gemma":0.002113988,"domain_scores_codex":[0.9990667,0.0002796604,0.00003910337,0.0001731072,0.000326499,0.0001151271],"domain_scores_gemma":[0.9980735,0.001283669,0.0001008649,0.0002595574,0.0002124385,0.00006988477],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002963158,0.00007366569,0.0001601148,0.0001995799,0.00004568226,0.00006952472,0.00005355052,0.8503747,0.003453277,0.04026907,0.008042543,0.09696198],"study_design_scores_gemma":[0.00002079525,0.00003541056,0.00004403399,0.000007897722,0.000008583621,0.00002156577,0.000006227749,0.9757722,0.0006594025,0.02205797,0.001362008,0.000003899761],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004028818,0.0003141589,0.983399,0.0001451527,0.0001040179,0.00004503273,0.00007599226,0.00043939,0.0114485],"genre_scores_gemma":[0.497504,0.001014156,0.4660353,0.0003537832,0.0003051906,0.000574841,0.0006050082,0.00113447,0.03247332],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01054058,"threshold_uncertainty_score":0.03526175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393921482220913,"score_gpt":0.2546079592798334,"score_spread":0.2406687444576242,"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."}}