{"id":"W4381089830","doi":"10.1016/j.dib.2023.109322","title":"Dataset of banana leaves and stem images for object detection, classification and segmentation: A case of Tanzania","year":2023,"lang":"en","type":"article","venue":"Data in Brief","topic":"Banana Cultivation and Research","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Styrelsen för Internationellt Utvecklingssamarbete; Makerere University; Harbin University of Science and Technology; International Development Research Centre; Rockefeller Foundation","keywords":"Crop; Fusarium wilt; Tanzania; Mycosphaerella; Cash crop; Fusarium oxysporum; Black spot; Fusarium oxysporum f.sp. cubense; Musaceae; Biology; Horticulture; Geography; Agronomy; Agriculture","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003638798,0.00003760323,0.00007522502,0.00002234433,0.00006167631,0.00001851235,0.00009037045,0.00002757507,0.00001254979],"category_scores_gemma":[0.00007115924,0.0000166649,0.000005836427,0.0003067845,0.0000746756,0.0001578731,0.00008350262,0.00002607035,7.100535e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003640657,"about_ca_system_score_gemma":0.000004216146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008114867,"about_ca_topic_score_gemma":0.00222745,"domain_scores_codex":[0.9995023,0.00003759938,0.0001544354,0.0001687019,0.00006707573,0.00006988059],"domain_scores_gemma":[0.9996207,0.0001828618,0.00005983309,0.00007562112,0.00003822801,0.00002273814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004340254,0.00003775955,0.01231065,0.0001000079,0.00001178411,0.000008277106,0.0001062206,6.202317e-7,0.5840699,0.0001030524,0.01201339,0.3911949],"study_design_scores_gemma":[0.0004852861,0.0001816397,0.9408073,0.00003057404,0.00001210912,0.00003982616,0.003781304,0.002438806,0.03748699,0.00007975304,0.01454719,0.000109227],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859012,0.00007708304,0.00002293632,0.0004360794,0.00001348769,0.0002164523,0.01331666,0.000006784173,0.000009307715],"genre_scores_gemma":[0.9938869,0.0001662854,0.0001107578,0.00001491429,0.0000166125,0.00001221691,0.005746963,4.678243e-7,0.00004483232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9284967,"threshold_uncertainty_score":0.124297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1229481043118909,"score_gpt":0.3413872244587279,"score_spread":0.218439120146837,"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."}}