{"id":"W2965387939","doi":"10.1609/socs.v10i1.18498","title":"Revisiting Suboptimal Search","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Bounded function; Search algorithm; Beam search; Iterative deepening depth-first search; Best-first search; Computer science; Mathematical optimization; Upper and lower bounds; Incremental heuristic search; Beam stack search; Bidirectional search; Node (physics); Search problem; Mathematics; Algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.001353408,0.0001592067,0.0002042237,0.00009183673,0.000203981,0.0003943967,0.002844098,0.00008504606,0.0000214287],"category_scores_gemma":[0.0004494086,0.0001335468,0.0001485053,0.0006352236,0.0000992108,0.0003918849,0.001480518,0.0004792001,0.00003974268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002196613,"about_ca_system_score_gemma":0.0001774002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003295634,"about_ca_topic_score_gemma":5.086331e-8,"domain_scores_codex":[0.9969089,0.0000445183,0.000354187,0.0005031929,0.001823912,0.0003653044],"domain_scores_gemma":[0.9977738,0.0002755331,0.0001327699,0.0002725965,0.001440558,0.0001047309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005186886,0.0002279016,0.007418774,0.00006031185,0.00009600996,0.00001948923,0.0005918851,0.001124336,0.1176625,0.8688948,0.0009349481,0.002917203],"study_design_scores_gemma":[0.001674531,0.0001873242,0.005990483,0.000580999,0.00001577921,0.0001566495,0.0001700579,0.09403087,0.8831698,0.01059099,0.002984462,0.0004480229],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7619923,0.0001096562,0.005030813,0.06607684,0.01623614,0.0006776343,0.00002117353,0.0003642287,0.1494912],"genre_scores_gemma":[0.9862417,0.00001654567,0.01190155,0.0001860526,0.0007616655,0.00001052492,0.000002505581,0.00001885266,0.0008605742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8583037,"threshold_uncertainty_score":0.5445881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214453960801229,"score_gpt":0.2754653915602443,"score_spread":0.253320851952232,"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."}}