{"id":"W1594463172","doi":"10.5555/2484920.2485009","title":"Stratified tree search: a novel suboptimal heuristic search algorithm","year":2013,"lang":"en","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina; University of Alberta","funders":"","keywords":"Beam search; Incremental heuristic search; Heuristics; Best-first search; Heuristic; Search algorithm; Benchmark (surveying); Algorithm; Computer science; Bidirectional search; Partition (number theory); Depth-first search; Search tree; Null-move heuristic; Iterative deepening depth-first search; Beam stack search; Tree traversal; Consistent heuristic; Mathematical optimization; Mathematics; Combinatorics","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":[0.0005080629,0.0001731083,0.0001664481,0.0001309542,0.0002140836,0.0005610356,0.0009138783,0.00008089084,0.0003495243],"category_scores_gemma":[0.00002657076,0.0001462089,0.00005966775,0.0003982346,0.00005875886,0.0005427986,0.0002421519,0.0003346305,0.0009090941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003148596,"about_ca_system_score_gemma":0.0001876638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001192764,"about_ca_topic_score_gemma":0.00001356743,"domain_scores_codex":[0.9981419,0.00007722416,0.0002353974,0.000468522,0.0004718709,0.0006050716],"domain_scores_gemma":[0.9986996,0.0003007117,0.00003049663,0.0005566262,0.0001655691,0.0002469899],"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":[0.0000131549,0.0004613904,0.002183795,0.00009773769,0.0001040931,0.000114764,0.004116829,0.006604158,0.01153633,0.05935485,0.02656864,0.8888443],"study_design_scores_gemma":[0.0003562122,0.0001657409,0.003506443,0.00002122555,0.000002774849,0.00002935088,0.00008277185,0.9929301,0.001806716,0.0005562981,0.0002973853,0.0002450561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01108881,0.00004420703,0.9715958,0.001568612,0.0001241544,0.0002323199,0.000005231442,0.0003258513,0.01501502],"genre_scores_gemma":[0.4386062,0.000002025822,0.5566956,0.0002886429,0.00007904664,0.00001861833,0.000008836138,0.00001198315,0.004289027],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9863259,"threshold_uncertainty_score":0.9998688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04620001475153443,"score_gpt":0.2618127690073549,"score_spread":0.2156127542558205,"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."}}