{"id":"W4396733110","doi":"10.3390/jimaging10050114","title":"A New Dataset and Comparative Study for Aphid Cluster Detection and Segmentation in Sorghum Fields","year":2024,"lang":"en","type":"article","venue":"Journal of Imaging","topic":"Date Palm Research Studies","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Segmentation; Computer science; Aphid; Sorghum; Blight; Image segmentation; Object detection; Cluster (spacecraft); Artificial intelligence; Pattern recognition (psychology); Infestation; Agronomy; 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":[0.0006457394,0.00179753,0.0009484225,0.003476919,0.001058148,0.001295743,0.001626312,0.001485096,0.002386051],"category_scores_gemma":[0.001434087,0.0003280093,0.001304394,0.002648565,0.0005040005,0.001181584,0.001027572,0.0007536713,0.002487808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001345139,"about_ca_system_score_gemma":0.001164178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0328004,"about_ca_topic_score_gemma":0.07625643,"domain_scores_codex":[0.9989864,0.00007163152,0.0001039699,0.0004298635,0.0002455045,0.0001624914],"domain_scores_gemma":[0.9992662,0.0001404857,0.00006268915,0.0001730157,0.0002727709,0.00008484495],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002457217,0.002282982,0.03630995,0.005328341,0.0006310377,0.002419598,0.0009509947,0.02262221,0.1062416,0.002092784,0.3794281,0.4392352],"study_design_scores_gemma":[0.000551613,0.001255578,0.2919834,0.0009013423,0.0005593365,0.005456409,0.003943233,0.2575534,0.08317743,0.003097815,0.3510788,0.0004415703],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6208031,0.00872244,0.02925267,0.001241869,0.001548538,0.001381269,0.2941577,0.02415857,0.0187338],"genre_scores_gemma":[0.244706,0.001518499,0.07620004,0.0004886791,0.000161066,0.0006723953,0.6709193,0.0006827365,0.00465133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0328004,"threshold_uncertainty_score":0.06521899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05872605559355376,"score_gpt":0.3561007191060127,"score_spread":0.2973746635124589,"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."}}