{"id":"W4396713641","doi":"10.1007/978-3-031-59057-3_14","title":"Multi-UAV Weed Spraying","year":2024,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Plant Surface Properties and Treatments","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"MD Precision (Canada); University of Regina","funders":"","keywords":"Weed; Computer science; Botany; Biology","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":[0.00005623965,0.0003653829,0.0003158055,0.0002243376,0.0001652719,0.0002278371,0.0003280881,0.0002571172,0.00398632],"category_scores_gemma":[0.0000502337,0.0001264834,0.000238668,0.0002169102,0.00009139328,0.0002884549,0.000332293,0.0002394073,0.0006717446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002018594,"about_ca_system_score_gemma":0.000116447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001307681,"about_ca_topic_score_gemma":0.003407436,"domain_scores_codex":[0.9999492,0.000003967746,0.0000011806,0.00001304823,0.00002325999,0.000009372315],"domain_scores_gemma":[0.9999781,0.000004795194,0.000003409261,0.000004333267,0.000005137369,0.000004174629],"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":[0.0001937374,0.00009366286,0.0005460418,0.0002312856,0.00003703903,0.0001699838,0.00004433258,0.01991008,0.6046107,0.002269116,0.004921041,0.366973],"study_design_scores_gemma":[0.00008090785,0.001590254,0.01958346,0.0001305019,0.0001100654,0.001340088,0.0001876303,0.3934698,0.4051519,0.005004892,0.173283,0.00006754078],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3257454,0.01497384,0.53488,0.0004663698,0.0008078152,0.0001950935,0.0005618008,0.003948225,0.1184214],"genre_scores_gemma":[0.8200531,0.003747022,0.09305321,0.0001641615,0.00006326214,0.00005948837,0.000274097,0.0001981571,0.08238756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00398632,"threshold_uncertainty_score":0.01333559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07048765134879477,"score_gpt":0.2657651272741424,"score_spread":0.1952774759253476,"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."}}