{"id":"W2898297778","doi":"10.1016/j.artint.2018.08.005","title":"Probably bounded suboptimal heuristic search","year":2018,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Bounded function; Heuristic; Mathematical optimization; Computer science; Incremental heuristic search; Mathematics; Artificial intelligence; Search algorithm; Beam search","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005592701,0.0001499732,0.0001384903,0.0001060164,0.000386323,0.0003997033,0.001049697,0.00005697558,0.0001862459],"category_scores_gemma":[0.0001779171,0.0001382447,0.00005781071,0.000637415,0.0002776387,0.0002738553,0.00027464,0.0002611534,0.003114474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003086774,"about_ca_system_score_gemma":0.0001036032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002220818,"about_ca_topic_score_gemma":0.00004663572,"domain_scores_codex":[0.9982376,0.0001095614,0.0002963153,0.0005080434,0.0003618986,0.000486614],"domain_scores_gemma":[0.9989089,0.0001125288,0.00005401468,0.000564346,0.0002173219,0.0001428774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001664054,0.0001113198,0.0002018012,0.000009389843,0.00001088703,0.00003154327,0.001542155,0.0004521541,0.001124267,0.5490407,0.0003299004,0.4471292],"study_design_scores_gemma":[0.00002018529,0.0004578236,0.0002798416,0.00002068723,0.000003980829,0.00003177382,0.00007099343,0.8430147,0.05076652,0.1011336,0.003897512,0.0003024399],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03363774,0.00003363946,0.9574596,0.001396087,0.000760854,0.0001312501,0.000001009586,0.0003130044,0.006266781],"genre_scores_gemma":[0.9265111,0.000003841395,0.07201348,0.0002517049,0.0005544905,0.000007813136,0.000001396222,0.00001110766,0.0006450629],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8928733,"threshold_uncertainty_score":0.9976617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05176550724848589,"score_gpt":0.323414968421788,"score_spread":0.2716494611733021,"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."}}