{"id":"W4404569055","doi":"10.48550/arxiv.2411.09731","title":"To bootstrap or to rollout? An optimal and adaptive interpolation","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Army Research Office; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Interpolation (computer graphics); Computer science; Econometrics; Mathematics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00636298,0.0006650476,0.001135122,0.0005880517,0.0005455121,0.00132603,0.001618996,0.001543312,0.002474089],"category_scores_gemma":[0.03626419,0.000523069,0.0007851346,0.0006094661,0.002422486,0.003615163,0.002222048,0.002627832,0.0002444989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069546,"about_ca_system_score_gemma":0.001706668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002391424,"about_ca_topic_score_gemma":0.001695077,"domain_scores_codex":[0.9973776,0.001407023,0.00008782691,0.0004752816,0.0004612376,0.0001910436],"domain_scores_gemma":[0.9894058,0.007602317,0.0007096617,0.001472266,0.0005553724,0.0002545354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002743705,0.0000956849,0.002705133,0.0001376054,0.00008243159,0.0001093901,0.0002651405,0.3650696,0.003538313,0.535794,0.002386895,0.08954135],"study_design_scores_gemma":[0.00001802313,0.0000529014,0.0002587627,0.00002833426,0.00001168539,0.00002624222,0.00002472782,0.8763833,0.00115466,0.1210611,0.000962329,0.00001794681],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01102248,0.0001317595,0.9872425,0.0004736976,0.00003213204,0.00002287543,0.00002733964,0.0001444557,0.0009029381],"genre_scores_gemma":[0.6342692,0.0003120172,0.3620969,0.0005886373,0.00009568404,0.0002055902,0.0001123396,0.000146186,0.002173504],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00636298,"threshold_uncertainty_score":0.03365105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3596239622221302,"score_gpt":0.346796632024632,"score_spread":0.01282733019749821,"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."}}