{"id":"W2361385409","doi":"","title":"Analysis on Combining Ability of Major Quality Characters in Three-line Indica Hybrid Rice of South China","year":2008,"lang":"en","type":"article","venue":"Seed","topic":"GABA and Rice Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biotechnology; Biology; Quality (philosophy); China; Selection (genetic algorithm); Line (geometry); Horticulture; Mathematics; Computer science; Artificial intelligence; Geography","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":[0.0006785479,0.00007811014,0.0003250606,0.00005079862,0.00006739787,0.000004190776,0.0001973214,0.00004420222,0.00005952724],"category_scores_gemma":[0.0001248565,0.00002861852,0.0001483132,0.0009853558,0.0001282928,0.00003789928,0.00004742654,0.0001456422,0.000005496208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001638664,"about_ca_system_score_gemma":0.00001092652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002755822,"about_ca_topic_score_gemma":0.0004037921,"domain_scores_codex":[0.9988161,0.0001515412,0.0003187064,0.0002049428,0.0003195363,0.0001891768],"domain_scores_gemma":[0.9994543,0.0001957512,0.0001608119,0.00008048913,0.00004851857,0.00006019212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008850278,0.0002399448,0.7756898,0.00001391912,0.00004223568,0.000002613647,0.000333806,0.00001081656,0.2229344,0.00002051755,7.011355e-7,0.0006227316],"study_design_scores_gemma":[0.0001847275,0.0001838279,0.9940211,0.000007154886,0.00001561883,4.058596e-7,0.0001646822,0.00009223155,0.005176568,0.00008856467,0.00000107855,0.00006400566],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992008,0.00001529318,0.000001767856,0.0003690714,0.00001278657,0.0001114303,0.00005321376,0.00001020571,0.0002254535],"genre_scores_gemma":[0.999864,0.00001019857,0.00001238774,0.00001750812,0.00001850484,0.00000242962,0.00004953728,3.936361e-7,0.00002503378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2183314,"threshold_uncertainty_score":0.4165997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04418935824439333,"score_gpt":0.2855024553302791,"score_spread":0.2413130970858857,"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."}}