{"id":"W4415614611","doi":"10.1186/s13007-025-01456-8","title":"Visual-language transformer-based tomato leaf disease detection for portable greenhouse monitoring device","year":2025,"lang":"en","type":"article","venue":"Plant Methods","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Khalifa University of Science, Technology and Research","keywords":"Preprocessor; Greenhouse; Adaptation (eye); Pixel; Precision and recall; Image (mathematics); Plant disease","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":[0.000403969,0.0001559127,0.0001875725,0.00002166193,0.0002626852,0.00006051923,0.000136684,0.00008416103,0.00003624279],"category_scores_gemma":[0.00008854536,0.00005904844,0.0001439402,0.0003600602,0.00001320359,0.0001011771,0.00001023611,0.00008520464,0.000004449075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002377368,"about_ca_system_score_gemma":0.00001362724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001897616,"about_ca_topic_score_gemma":0.0003098699,"domain_scores_codex":[0.9990163,0.0001118089,0.0001978703,0.000279762,0.0001103439,0.0002838759],"domain_scores_gemma":[0.9991626,0.0005836527,0.00005081583,0.00004638865,0.00004205081,0.0001144898],"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":[0.0001433941,0.00008249462,0.005104355,0.00005413436,0.00002138781,0.000005058471,0.00004384068,0.00001401926,0.7593736,0.00003093359,0.0002493946,0.2348774],"study_design_scores_gemma":[0.0003143931,0.0001449269,0.1069359,0.00009904049,0.0001187215,0.00000240984,0.0004763058,0.001261685,0.8386531,0.0001714326,0.05153009,0.0002920251],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845914,0.0006189953,0.01268294,0.0005089753,0.0004724639,0.0004680631,0.000109638,0.0002116783,0.0003357916],"genre_scores_gemma":[0.9898153,0.00002002901,0.008393239,0.0003280445,0.000464015,0.0001740014,0.0001499439,0.000001804308,0.000653616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2345854,"threshold_uncertainty_score":0.2407925,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02632479183424611,"score_gpt":0.3360778240971091,"score_spread":0.3097530322628629,"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."}}