{"id":"W4312205635","doi":"10.3390/agriculture13010056","title":"Optimal Path Generation with Obstacle Avoidance and Subfield Connection for an Autonomous Tractor","year":2022,"lang":"en","type":"article","venue":"Agriculture","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Korea Institute of Industrial Technology","keywords":"Tractor; Tree traversal; Path (computing); Computer science; Field (mathematics); Range (aeronautics); Obstacle; Process (computing); Mathematical optimization; Mathematics; Algorithm; Engineering; Automotive engineering; Aerospace engineering","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":[0.0001468585,0.000587117,0.0003571975,0.0004423542,0.0003724392,0.0002958468,0.0005824436,0.0004561229,0.001882982],"category_scores_gemma":[0.0003563051,0.0002757596,0.000405124,0.0003742668,0.0002654985,0.0004700211,0.0005600503,0.0003920416,0.0003524574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004591625,"about_ca_system_score_gemma":0.001028536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006954678,"about_ca_topic_score_gemma":0.009743113,"domain_scores_codex":[0.9998742,0.00001719405,0.000004072898,0.00003712123,0.00004358481,0.00002375036],"domain_scores_gemma":[0.9998672,0.00004356841,0.0000231856,0.00002289328,0.00002831868,0.00001475023],"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":[0.000158894,0.00008146046,0.001422899,0.00006676235,0.00003276699,0.0001497666,0.0001669139,0.7391824,0.02697985,0.003874309,0.00167162,0.2262124],"study_design_scores_gemma":[0.000009718186,0.00005029581,0.0003236513,0.000002299084,0.000004541619,0.00004525114,0.00002049487,0.9948065,0.002872396,0.000766015,0.001091245,0.000007621347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0832053,0.000118021,0.911354,0.00008660759,0.00002326288,0.00007670929,0.00007105609,0.001457762,0.003607284],"genre_scores_gemma":[0.4798025,0.00008511262,0.5153822,0.00003173918,0.000007273791,0.0001040535,0.0001916722,0.0001082655,0.004287064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006954678,"threshold_uncertainty_score":0.0138284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01935262741534247,"score_gpt":0.2222278410516496,"score_spread":0.2028752136363071,"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."}}