{"id":"W2380619239","doi":"","title":"Molecular Identification of High Quality Subunit 1 Dx 5+1 Dy 10 in Wheat Backcrossing Progenies","year":2009,"lang":"en","type":"article","venue":"Seed","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Glutenin; Backcrossing; Molecular marker; Marker-assisted selection; Selection (genetic algorithm); Biology; Protein subunit; Botany; Gene; Genetics; Genetic marker; Artificial intelligence; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001447304,0.0003257084,0.0001540669,0.0004133372,0.0001775617,0.0002547042,0.0001639592,0.0002328206,0.001792664],"category_scores_gemma":[0.0001624967,0.0001877222,0.0002035319,0.0001231848,0.0001303664,0.0001117027,0.000199535,0.0003657785,0.0004180442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001835256,"about_ca_system_score_gemma":0.0001096103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005482064,"about_ca_topic_score_gemma":0.001570216,"domain_scores_codex":[0.9998803,0.00001197035,0.00001032137,0.00004282276,0.00003434342,0.00002016246],"domain_scores_gemma":[0.9998519,0.00002886837,0.00003939297,0.00001858594,0.00001972253,0.00004142755],"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":[0.00001704571,0.000008278287,0.001039728,0.000008445757,0.000002913789,0.0000704002,0.00002329403,0.000005469093,0.9978054,0.00002529462,0.000005370631,0.0009884845],"study_design_scores_gemma":[0.00003779669,0.0006617664,0.3191349,0.00002120245,0.0001406351,0.003230945,0.0002460381,0.00069855,0.6700919,0.0001204357,0.005594562,0.00002120831],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965808,0.0001623647,0.002423703,0.00001708973,0.000009153264,0.00001499047,0.0001161689,0.00003231569,0.0006434884],"genre_scores_gemma":[0.9908473,0.0002291992,0.003584464,0.00003586524,0.000005274113,0.00001965432,0.001138088,0.00003066494,0.004109322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001792664,"threshold_uncertainty_score":0.005997062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02312323043587055,"score_gpt":0.263291718389146,"score_spread":0.2401684879532754,"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."}}