{"id":"W2010185804","doi":"10.2478/s13230-012-0014-3","title":"Fuzzy Control of a Log Carrying Robot on Tree-Filled Steep-Sloping Terrains","year":2012,"lang":"en","type":"article","venue":"Paladyn Journal of Behavioral Robotics","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Terrain; Controller (irrigation); Fuzzy logic; Control theory (sociology); Computer science; Position (finance); Modular design; Fuzzy control system; Artificial intelligence; Simulation; Control engineering; Engineering; Control (management); Geography","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":[0.0012049,0.0003604508,0.0008750642,0.000458388,0.000141298,0.00009731072,0.001217954,0.000177109,0.000006636983],"category_scores_gemma":[0.0001272683,0.0003124433,0.0003608647,0.0004511933,0.0001122264,0.0007591028,0.000146895,0.0006533771,0.00001627133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001864722,"about_ca_system_score_gemma":0.000182351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001617773,"about_ca_topic_score_gemma":0.000001755451,"domain_scores_codex":[0.9964138,0.0002761132,0.001243462,0.000261051,0.001004013,0.0008015461],"domain_scores_gemma":[0.9969316,0.0002903398,0.001286018,0.0006182167,0.0004051168,0.0004686714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002169148,0.002707112,0.1825987,0.0001224735,0.0003409031,0.0006902386,0.01111003,0.7007489,0.02138999,0.006628402,0.0004930622,0.07295332],"study_design_scores_gemma":[0.03730367,0.01890511,0.525721,0.007237564,0.00348404,0.007746876,0.004618708,0.3663718,0.01881562,0.002507336,0.0006350491,0.006653192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06227959,0.0006076655,0.9327373,0.0005384933,0.003003975,0.0002605576,0.000008146652,0.00006522982,0.0004990715],"genre_scores_gemma":[0.771081,0.00001332906,0.2284119,0.00009914475,0.0003222252,0.000002420425,0.000001350811,0.00002702714,0.0000416529],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7088014,"threshold_uncertainty_score":0.9999328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04889827704974042,"score_gpt":0.3051850944416111,"score_spread":0.2562868173918706,"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."}}