{"id":"W4408712625","doi":"10.1038/s41597-025-04456-4","title":"Banana Leaves Imagery Dataset","year":2025,"lang":"en","type":"article","venue":"Scientific Data","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"International Development Research Centre; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Tanzania; Fusarium wilt; Agriculture; Data collection; Geography; Race (biology); Computer science; Remote sensing; Cartography; Horticulture; Biology; Botany; Environmental planning; Statistics; Mathematics","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":[0.0005550143,0.00009973826,0.0001077238,0.00001784341,0.0004642998,0.0005088312,0.00167148,0.00004317009,0.0007242972],"category_scores_gemma":[0.0001069449,0.00003126922,0.00002952431,0.0008759957,0.0001591772,0.0004562352,0.0009812728,0.00008005949,0.0004436742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007576521,"about_ca_system_score_gemma":0.00001652029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001440843,"about_ca_topic_score_gemma":0.001243135,"domain_scores_codex":[0.9986724,0.00003542228,0.0001544699,0.0006801151,0.0002007138,0.0002568497],"domain_scores_gemma":[0.9992644,0.0000907928,0.00003669045,0.0005060803,0.00003925514,0.00006282175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002177318,0.00003525248,0.0007537417,0.00000275081,0.000006270054,0.000002713121,0.000004522265,1.039021e-7,0.04661497,0.0002077135,0.9161739,0.03619593],"study_design_scores_gemma":[0.00003732463,0.000007043217,0.03239394,0.00001426688,0.00001283633,0.000001309417,0.0001240056,0.00002619915,0.002095705,0.000383502,0.9648075,0.00009641528],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6532779,0.002986727,0.00005465366,0.0368077,0.01213704,0.0009829156,0.2506935,0.0005549609,0.04250458],"genre_scores_gemma":[0.4854922,0.00005435267,0.0005198012,0.003299263,0.0009969672,0.00001712397,0.4484158,0.000001332909,0.0612031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1977223,"threshold_uncertainty_score":0.7930546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04199163189997691,"score_gpt":0.266679057582406,"score_spread":0.2246874256824291,"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."}}