{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002839867,0.00003585805,0.00007426058,0.000023966,0.00004865023,0.0001073709,0.00003005126,0.000006171024,0.000006340169],"category_scores_gemma":[0.00002539837,0.00001311612,0.00001056446,0.00007465381,0.00001246966,0.0002367741,0.00003455759,0.00007180319,3.163977e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001079121,"about_ca_system_score_gemma":0.000003425708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001064169,"about_ca_topic_score_gemma":0.0009831963,"domain_scores_codex":[0.9996551,0.00003155189,0.0001092708,0.00006615771,0.00007431826,0.00006359629],"domain_scores_gemma":[0.999731,0.0001825785,0.00002947162,0.000007475364,0.00002203922,0.00002743788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002788588,0.00010297,0.06818683,0.00006173842,0.0001016,0.00004679782,0.005390855,0.00001391265,0.1218498,0.00000995408,0.02011085,0.7838458],"study_design_scores_gemma":[0.002637213,0.002839714,0.8915479,0.0003208141,0.0001077144,0.0002247371,0.06074543,0.01235065,0.006819241,0.002347272,0.01972064,0.0003386336],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964274,0.0008492044,0.000355933,0.00209815,0.0000569002,0.0001637302,0.00003161288,0.000002624024,0.00001450947],"genre_scores_gemma":[0.9996046,0.00006257556,0.0001765399,0.00003763695,0.00009493005,0.000002525478,0.000006393472,1.804322e-7,0.00001457571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8233611,"threshold_uncertainty_score":0.103538,"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."}}