{"id":"W4414111555","doi":"10.12688/f1000research.166848.1","title":"Identifying Adaptable Varieties of Sorghum (Sorghum bicolor L) in Tidal Swamplands and Sandy Soils by MGIDI and GGE Biplots","year":2025,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute on Governance","funders":"","keywords":"Sorghum; Adaptability; Biplot; Forage; Randomized block design; Arable land; Soil water; Crop","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001037402,0.0006214085,0.0007455212,0.002366039,0.0005104557,0.0008966979,0.0003865737,0.0002664464,0.002136222],"category_scores_gemma":[0.001349575,0.0001675394,0.001082561,0.001902998,0.0004063563,0.0002458875,0.0005676302,0.0006799932,0.0002716017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000566762,"about_ca_system_score_gemma":0.0004744871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005589695,"about_ca_topic_score_gemma":0.00684454,"domain_scores_codex":[0.9989573,0.000312341,0.00006821364,0.0003528047,0.000157986,0.0001513184],"domain_scores_gemma":[0.9986877,0.000664317,0.00017293,0.0001043214,0.0001647399,0.0002059451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01597285,0.0032313,0.4398828,0.0006170115,0.001458022,0.001106,0.00145598,0.008813858,0.3972167,0.0009840182,0.002485444,0.126776],"study_design_scores_gemma":[0.0000914597,0.001338298,0.9726899,0.0000184696,0.0001452451,0.0002237723,0.0007096625,0.01381414,0.008507261,0.0001409869,0.002265055,0.00005584371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942535,0.00006278348,0.002666976,0.0000259315,0.00001234237,0.00004479771,0.002355129,0.0001098065,0.0004687854],"genre_scores_gemma":[0.9791934,0.000049046,0.0130891,0.00002827121,0.00000551231,0.0002107199,0.00638978,0.00007311931,0.0009610142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005589695,"threshold_uncertainty_score":0.0111143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03142234283014934,"score_gpt":0.3002702574150579,"score_spread":0.2688479145849086,"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."}}