{"id":"W2133482720","doi":"10.1007/978-3-540-72665-4_46","title":"Hierarchical Shortest Pathfinding Applied to Route-Planning for Wheelchair Users","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pathfinding; Computer science; Dijkstra's algorithm; Shortest path problem; Mathematical optimization; Motion planning; Algorithm; Theoretical computer science; Artificial intelligence; Mathematics; Robot","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002247263,0.0008474353,0.0008867544,0.001871449,0.0005119963,0.0007691459,0.004851798,0.0005582456,0.000004257122],"category_scores_gemma":[0.0002295816,0.0008380731,0.0001912267,0.001045892,0.0004437657,0.0004117478,0.001577291,0.001289414,0.00004937278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00061678,"about_ca_system_score_gemma":0.0006480898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001116443,"about_ca_topic_score_gemma":0.00001087399,"domain_scores_codex":[0.9934092,0.00002429746,0.0008482948,0.002622635,0.001472996,0.001622638],"domain_scores_gemma":[0.9956748,0.001539056,0.0003134742,0.001658293,0.0002351247,0.0005792687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000205853,0.0000302691,0.0001849108,0.00004106377,0.00002036846,0.0002471717,0.002505139,0.4087162,0.0002479667,0.02276053,0.00007460441,0.5651512],"study_design_scores_gemma":[0.0005580359,0.0004303388,0.0005151537,0.0009210721,0.00001719105,0.0001424119,9.769526e-7,0.9434274,0.001022268,0.04820241,0.003059747,0.001702996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008085214,0.0001090962,0.9914627,0.0005875787,0.002714407,0.001156687,0.00001554248,0.0004095884,0.003463542],"genre_scores_gemma":[0.03486074,0.000002313406,0.9610433,0.002777999,0.0009556287,0.00004360684,0.00001728856,0.0000775618,0.0002215648],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5634482,"threshold_uncertainty_score":0.999407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04220036228549223,"score_gpt":0.2939609903223324,"score_spread":0.2517606280368402,"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."}}