{"id":"W2293312031","doi":"10.1109/csci.2015.92","title":"C-Theta*: Cluster Based Path-Planning on Grids","year":2015,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Grid; Motion planning; Shortest path problem; Path (computing); Computer science; Cluster analysis; Constraint (computer-aided design); Widest path problem; Grid reference; Any-angle path planning; Grid method multiplication; Algorithm; Cluster (spacecraft); Path length; Mathematical optimization; K shortest path routing; Mathematics; Artificial intelligence; Theoretical computer science; Mobile robot; Graph; Geometry","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":[0.0006072819,0.0001623064,0.0001569825,0.0001377806,0.00006753259,0.0001529714,0.0007941286,0.0000701044,0.0000105626],"category_scores_gemma":[0.0001018196,0.000128484,0.00004779706,0.0003019112,0.00002435409,0.0002650163,0.0001373112,0.0001659761,0.000682967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005484827,"about_ca_system_score_gemma":0.0001186764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001347244,"about_ca_topic_score_gemma":9.832894e-8,"domain_scores_codex":[0.9984853,0.00009777582,0.0001869996,0.0003980543,0.0004804907,0.000351324],"domain_scores_gemma":[0.9987737,0.0001524077,0.00005759639,0.0006911732,0.00007972878,0.000245391],"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":[0.00006045932,0.0004025991,0.00889792,0.00002583669,0.00004647185,0.0007496311,0.004509936,0.5644017,0.0001694258,0.02431786,0.3700699,0.02634821],"study_design_scores_gemma":[0.0007253066,0.0002460902,0.001097066,0.00004457462,0.000002944626,0.00002147834,0.00003616583,0.990795,0.0004850304,0.0009115892,0.0053969,0.0002378829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001796525,0.00002623331,0.9416986,0.001467477,0.001130142,0.0001029848,8.791196e-7,0.0004911261,0.05328609],"genre_scores_gemma":[0.2722112,2.088996e-7,0.7184126,0.005793897,0.0002568099,0.00001624303,0.000005946892,0.00002102321,0.003281994],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4263932,"threshold_uncertainty_score":0.8778387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06172175499465651,"score_gpt":0.2878198593003833,"score_spread":0.2260981043057268,"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."}}