{"id":"W4403990817","doi":"10.5376/gab.2024.15.0027","title":"Development of High-Throughput Molecular Markers for Soybean Breeding","year":2024,"lang":"en","type":"article","venue":"Genomics and Applied Biology","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Throughput; Biology; Molecular breeding; Biotechnology; Genetics; Computer science; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012749,0.00007398932,0.0001026069,0.000008423272,0.00006953232,0.00001993695,0.00006383113,0.00006929388,0.00001565225],"category_scores_gemma":[0.000002601085,0.00003211481,0.0000270568,0.00006200434,0.0000358424,0.000006507044,0.00004439949,0.00002772316,0.000002068349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001105198,"about_ca_system_score_gemma":0.000009228893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007116953,"about_ca_topic_score_gemma":0.00001311949,"domain_scores_codex":[0.9994847,0.000004091184,0.0001506845,0.0002054913,0.0000245691,0.0001304436],"domain_scores_gemma":[0.9998608,0.00004628505,0.00003176666,0.0000198803,0.00001437517,0.0000268587],"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":[0.00001089644,0.000005019595,0.00003244509,0.000009101434,0.00001705794,6.884166e-8,0.00006966761,0.000001414338,0.7608841,0.02903426,0.0000329365,0.209903],"study_design_scores_gemma":[0.0005090116,0.0004844969,0.01846131,0.00003502657,0.00005062832,0.000005042529,0.00157941,0.0006889756,0.6255919,0.05899889,0.2929728,0.0006225395],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979239,0.0002646064,0.001012852,0.0001967696,0.00008991725,0.0001723875,0.00003167308,0.00001636765,0.0002915958],"genre_scores_gemma":[0.9906112,0.00002940072,0.009042244,0.00007342966,0.00008798773,0.00002350491,0.0001170031,0.000001114209,0.00001409144],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2929398,"threshold_uncertainty_score":0.1309604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01795442556006798,"score_gpt":0.2175328208589246,"score_spread":0.1995783952988566,"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."}}