{"id":"W4378965586","doi":"10.18280/jesa.560210","title":"Mission-Planner Mapped Autonomous Robotic Lawn Mower","year":2023,"lang":"fr","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Robotics and Automated Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lawn; Planner; Computer science; Artificial intelligence; Human–computer interaction; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001105004,0.0003583668,0.0003427104,0.0002172014,0.0002260094,0.0002859124,0.0006620743,0.000473705,0.002302052],"category_scores_gemma":[0.0002637176,0.000201356,0.0001819551,0.0001050177,0.0002243847,0.0004161665,0.0004920233,0.0004019963,0.0005858578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002019333,"about_ca_system_score_gemma":0.0004590866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001894495,"about_ca_topic_score_gemma":0.003119804,"domain_scores_codex":[0.9998714,0.00001124584,0.00000489672,0.00003449358,0.00006194881,0.00001600473],"domain_scores_gemma":[0.9998814,0.0000199738,0.00001674568,0.00002388855,0.00003969848,0.00001839901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003282404,0.0002760971,0.003037826,0.0004818081,0.00004109806,0.001470957,0.0005237859,0.06144401,0.672208,0.00384182,0.003350534,0.2529959],"study_design_scores_gemma":[0.0002836949,0.002522763,0.0182844,0.0001039973,0.00007230781,0.002709524,0.0004155186,0.5793409,0.3090325,0.002387849,0.08472577,0.0001207748],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3935695,0.0002875121,0.5832409,0.0001851894,0.00008361161,0.0005035991,0.000241329,0.006953231,0.01493514],"genre_scores_gemma":[0.8366534,0.0001129592,0.1389094,0.00006514731,0.0000116952,0.0002788044,0.0002438737,0.0001045961,0.0236202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002302052,"threshold_uncertainty_score":0.007701099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02496696572634288,"score_gpt":0.2543447915248583,"score_spread":0.2293778257985154,"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."}}