{"id":"W4399803839","doi":"10.4204/eptcs.403.16","title":"Uniform Sampling and Visualization of 3D Reluctant Walks","year":2024,"lang":"en","type":"article","venue":"Electronic Proceedings in Theoretical Computer Science","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Orthant; Random walk; Sampling (signal processing); Sample (material); Visualization; Mathematics; Statistical physics; Combinatorics; Computer science; Statistics; Data mining; Physics; Computer vision","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":[],"consensus_categories":[],"category_scores_codex":[0.001640148,0.0001349245,0.0001650575,0.0004698763,0.000115227,0.0005732856,0.0009671803,0.00004821986,0.000008176469],"category_scores_gemma":[0.0001288652,0.0001152441,0.00002300763,0.002745439,0.0008060684,0.001150968,0.000565419,0.0001882239,0.000003962331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001280653,"about_ca_system_score_gemma":0.0002424557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001778345,"about_ca_topic_score_gemma":5.434018e-7,"domain_scores_codex":[0.9980764,0.00001060644,0.0003320134,0.000600079,0.0004778687,0.0005030393],"domain_scores_gemma":[0.9994418,0.00007856493,0.00005570037,0.000165967,0.000161156,0.00009683563],"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":[0.000002062309,0.00002143709,0.0001095748,0.00004957962,0.000002770598,0.000001278867,0.0005437524,0.00002039041,0.0009710598,0.9773685,0.000007734874,0.0209018],"study_design_scores_gemma":[0.00008221388,0.0001430726,0.0001518414,0.0001225174,0.000003324329,0.00002953017,0.00001001118,0.7946551,0.002601468,0.201667,0.0004103529,0.0001234832],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01935734,0.0002636468,0.9781792,0.0003301342,0.0001553836,0.0001066718,7.761658e-7,0.0001610771,0.001445813],"genre_scores_gemma":[0.969103,0.0001299412,0.03056796,0.0001396818,0.00004071135,0.000002914179,0.000001172866,0.000008182403,0.000006424569],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9497457,"threshold_uncertainty_score":0.5528206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021162179528529,"score_gpt":0.2927010076531216,"score_spread":0.2824893858578363,"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."}}