{"id":"W9358471","doi":"10.1016/s1357-4310(97)01111-8","title":"OpenCL Implimentation of LiDAR Data Processing","year":2014,"lang":"en","type":"article","venue":"Molecular Medicine Today","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Obstacle; Obstacle avoidance; Data processing; Lidar; Architecture; Collision avoidance; Product (mathematics); Real-time computing; Embedded system; Artificial intelligence; Robot; Database; Computer security; Collision","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":[0.0008804852,0.0001112429,0.0002088793,0.00009678175,0.00005072988,0.00002064505,0.001378763,0.00003599475,0.000009195787],"category_scores_gemma":[0.0002600082,0.00009085572,0.00001464361,0.0003281538,0.00007157433,0.0002946112,0.0003853417,0.00009093131,0.0000150118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001379306,"about_ca_system_score_gemma":0.00005663369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005740231,"about_ca_topic_score_gemma":3.311201e-7,"domain_scores_codex":[0.9985966,0.0001008692,0.0002859028,0.0003875685,0.0004395165,0.0001895483],"domain_scores_gemma":[0.9984677,0.00005756332,0.000163174,0.001150259,0.00008100447,0.00008032141],"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":[0.000009357452,0.000123322,0.001449232,0.0002110467,0.00005969404,0.00012372,0.003345121,0.001192731,0.3470735,0.01339512,0.003670763,0.6293464],"study_design_scores_gemma":[0.001981197,0.0006619979,0.01219027,0.000709195,0.00008048626,0.0001056232,0.0001157465,0.9188524,0.05618267,0.002787523,0.005885059,0.0004478037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003652626,0.0003910884,0.9906536,0.002264541,0.0002079023,0.000116005,0.00000116667,0.000071141,0.002641918],"genre_scores_gemma":[0.6356896,0.000001960447,0.3633108,0.0007963416,0.00008227848,0.000004298627,0.00004057767,0.0000116004,0.00006253082],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9176597,"threshold_uncertainty_score":0.3704989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03390733785117129,"score_gpt":0.3185166103100542,"score_spread":0.2846092724588829,"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."}}