{"id":"W2397145713","doi":"","title":"Towards a second generation random walk planner: an experimental exploration","year":2013,"lang":"en","type":"article","venue":"","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Random walk; Planner; Computer science; Operator (biology); State space; Monte Carlo method; Mathematical optimization; Theoretical computer science; Mathematics; Artificial intelligence; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005641943,0.001464657,0.001054435,0.0009735567,0.000722141,0.001142842,0.001970215,0.001980403,0.007107087],"category_scores_gemma":[0.0157368,0.0004878527,0.0008128881,0.001219084,0.001249842,0.00263472,0.001773594,0.002130574,0.0008548256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001385768,"about_ca_system_score_gemma":0.001637231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004663367,"about_ca_topic_score_gemma":0.006151531,"domain_scores_codex":[0.996842,0.00178029,0.0001465416,0.0003556948,0.0005869133,0.0002885079],"domain_scores_gemma":[0.9823989,0.01441058,0.0003131223,0.001694349,0.0008865517,0.000296452],"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":[0.00449435,0.008605583,0.004809385,0.002615509,0.0003213982,0.0006023312,0.001637086,0.6961601,0.01084838,0.03970662,0.02208242,0.2081169],"study_design_scores_gemma":[0.001300827,0.004391721,0.001093995,0.0001142632,0.00008956082,0.0001693525,0.0005116403,0.9501181,0.01226797,0.01961309,0.01026234,0.00006719903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7406687,0.003435286,0.1972586,0.001890302,0.0004423126,0.00197688,0.003671926,0.00319114,0.04746481],"genre_scores_gemma":[0.7710783,0.0008236517,0.2163237,0.0004208288,0.00006901933,0.001181877,0.002489385,0.0004016308,0.007211517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007107087,"threshold_uncertainty_score":0.02983779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03980206178376905,"score_gpt":0.2581261735764433,"score_spread":0.2183241117926742,"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."}}