{"id":"W4409971382","doi":"10.5376/pgt.2024.15.0009","title":"&lt;i&gt;DEP1&lt;/i&gt; and Panicle Architecture: Influencing Rice Yield through Genetic Modulation","year":2024,"lang":"en","type":"article","venue":"Plant Gene and Trait","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Panicle; Yield (engineering); Agronomy; Biology; Physics","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":[0.00008257865,0.0001342201,0.0001403382,0.0000192541,0.000177249,0.00006983129,0.0000894478,0.0001405483,0.00005078607],"category_scores_gemma":[0.0000144306,0.0000583595,0.000038335,0.0001744741,0.00005771772,0.00008310143,0.00004451547,0.0001200116,0.00001263837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006049933,"about_ca_system_score_gemma":0.000004669485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004421611,"about_ca_topic_score_gemma":0.0006028573,"domain_scores_codex":[0.9991953,0.00002107709,0.0001502644,0.0003090794,0.00009473971,0.0002295583],"domain_scores_gemma":[0.9997062,0.0001602013,0.00002754581,0.00004418652,0.00001109231,0.00005074103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001605497,0.00001389137,0.0007600423,0.00002097764,0.00002867645,0.00002829267,0.0001996056,0.00001326636,0.8962625,0.0014831,0.0001304417,0.1010431],"study_design_scores_gemma":[0.000422131,0.0005399592,0.919038,0.000137943,0.00015955,0.0005803249,0.0001150507,0.004265964,0.01666234,0.01826794,0.03918676,0.0006240122],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912301,0.006542358,0.0001063821,0.001265061,0.00006154046,0.0001359257,0.0001187566,0.000201777,0.0003381486],"genre_scores_gemma":[0.9987072,0.0006528654,0.0001767767,0.0002392013,0.0001133402,0.00001306275,0.00003035098,0.000001743061,0.00006541159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.918278,"threshold_uncertainty_score":0.2379832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01523016301020701,"score_gpt":0.1926736190986367,"score_spread":0.1774434560884297,"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."}}