{"id":"W7133116061","doi":"","title":"Empirical Models of Heuristic Search in AI Planning and Neural Sequence Decoding","year":2021,"lang":"","type":"dissertation","venue":"TSpace","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"Beam search; Heuristic; Incremental heuristic search; Decoding methods; Search algorithm; Satisficing; Empirical research; Sequence (biology)","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003943211,0.000307445,0.0004952106,0.0004445655,0.0001544368,0.0002528947,0.0002928065,0.000261598,0.00008935163],"category_scores_gemma":[0.0001627283,0.0003673312,0.00007759526,0.0009257705,0.0001167642,0.0005445729,0.0001519899,0.0007176399,0.000001770231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000106127,"about_ca_system_score_gemma":0.0006133189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003327208,"about_ca_topic_score_gemma":0.0001954474,"domain_scores_codex":[0.9974504,0.0002842312,0.0005983802,0.0007714037,0.0004985498,0.000397074],"domain_scores_gemma":[0.998607,0.0003376154,0.0002360395,0.0003324942,0.0003244698,0.0001624244],"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":[0.00009162324,0.0000854327,0.04229823,0.0006516351,0.00003637368,0.0002527062,0.1116566,0.7883841,0.002403833,0.002636878,0.00003680679,0.05146576],"study_design_scores_gemma":[0.0003552368,0.00005806717,0.01669554,0.0006501105,0.00001688146,0.00004784446,0.006112149,0.9749202,0.0005956651,0.0002430341,0.000003773013,0.0003014546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5462208,0.0009211741,0.4504953,0.0007833368,0.000429725,0.0002559209,0.000003891415,0.00003122739,0.0008585653],"genre_scores_gemma":[0.9882216,0.0002137303,0.01079117,0.0001417123,0.00002748496,0.000008233374,0.00005945408,0.00001895204,0.0005176351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4420008,"threshold_uncertainty_score":0.9998779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1220743046594857,"score_gpt":0.4282263411095157,"score_spread":0.30615203645003,"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."}}