{"id":"W2259697407","doi":"10.1145/2822013.2822043","title":"ACCLMesh","year":2015,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of British Columbia","funders":"","keywords":"Polygon mesh; Computer science; Collision avoidance; Curvature; Computer vision; Artificial intelligence; Computer graphics (images); Collision; Geometry; Mathematics","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":[0.0004000583,0.0009702907,0.0005294217,0.001372387,0.0009302399,0.00180076,0.002247796,0.001406293,0.05945368],"category_scores_gemma":[0.002007994,0.0005241907,0.0006514312,0.0008222383,0.0004634937,0.001480361,0.002686506,0.00144304,0.03502611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006687017,"about_ca_system_score_gemma":0.001167224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005078172,"about_ca_topic_score_gemma":0.008805651,"domain_scores_codex":[0.9993193,0.00007310548,0.00003329083,0.0001503628,0.0003596261,0.00006435067],"domain_scores_gemma":[0.999334,0.0000865764,0.00003261782,0.0002763392,0.0002191855,0.00005113657],"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":[0.0001851534,0.00006266309,0.0008639037,0.0003317876,0.00004571702,0.0002907514,0.0001482834,0.05049105,0.01308663,0.06951693,0.162429,0.7025482],"study_design_scores_gemma":[0.00005720415,0.00003806263,0.0004694983,0.00007381209,0.00001721989,0.000411451,0.00005102556,0.4838676,0.01808613,0.03411473,0.4627458,0.00006747711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004052982,0.0004468588,0.8829998,0.0005352811,0.000730277,0.0001603417,0.001875537,0.03258795,0.07661092],"genre_scores_gemma":[0.1060841,0.0006172141,0.7563688,0.0008364416,0.0002131899,0.0006255363,0.008961664,0.008261873,0.1180313],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05945368,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07000709988147788,"score_gpt":0.2734060782686126,"score_spread":0.2033989783871347,"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."}}