{"id":"W4387564952","doi":"10.20944/preprints202310.0386.v1","title":"Stream Function-Based Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Obstacle avoidance; Underwater; Robustness (evolution); Computer science; Adaptability; Collision avoidance; Function (biology); Curvature; Algorithm; Real-time computing; Artificial intelligence; Mobile robot; Robot; Mathematics; Collision; Geology","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001229352,0.0006824722,0.0007061056,0.0003489173,0.0003392792,0.0002248283,0.002838397,0.0005602535,0.00004109294],"category_scores_gemma":[0.0002347696,0.0007292163,0.0004209591,0.0003600959,0.0001270436,0.0002719794,0.002671891,0.001034452,0.002222746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004128052,"about_ca_system_score_gemma":0.0007535859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002763999,"about_ca_topic_score_gemma":0.00000740893,"domain_scores_codex":[0.9949186,0.0002012135,0.0008269224,0.002430777,0.0006626452,0.0009598387],"domain_scores_gemma":[0.9951265,0.0006557262,0.0005170283,0.003073162,0.0003437326,0.0002837954],"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":[0.00007245819,0.0008873939,0.08901207,0.0009929702,0.000940248,0.0002432912,0.002213019,0.6870744,0.001867938,0.001409787,0.002008574,0.2132778],"study_design_scores_gemma":[0.0007814048,0.00007407308,0.07862522,0.000284192,0.00006825032,0.000007264813,0.0000320727,0.8936037,0.01092591,0.01267883,0.002014693,0.0009044083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02144217,0.00009294328,0.9687352,0.001258757,0.004374441,0.001281657,0.0001349972,0.00240273,0.00027711],"genre_scores_gemma":[0.3640072,0.00002004756,0.6237799,0.0007278881,0.0008874576,0.001914781,0.0003527713,0.0002404745,0.008069482],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3449553,"threshold_uncertainty_score":0.9995159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1377018478512035,"score_gpt":0.3312111090500035,"score_spread":0.1935092611988,"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."}}