{"id":"W2083303134","doi":"10.1093/nar/gkj012","title":"OryGenesDB: a database for rice reverse genetics","year":2005,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centre de Coopération Internationale en Recherche Agronomique pour le Développement; International Development Research Centre","keywords":"Genome browser; Biology; Genome; Insertional mutagenesis; Genomics; Functional genomics; Genetics; Database; Computational biology; Gene; Comparative genomics; Reference genome; Ensembl; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006507541,0.00009435856,0.0001031631,0.00002213167,0.0004963441,0.00007309899,0.0005652559,0.00008948927,0.001412948],"category_scores_gemma":[0.000276353,0.00003987239,0.00007048897,0.000488634,0.00008833843,0.00008489294,0.0002775965,0.0001644977,0.0004805646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004796967,"about_ca_system_score_gemma":0.00002791902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008886844,"about_ca_topic_score_gemma":0.0004676323,"domain_scores_codex":[0.9985154,0.0001000103,0.0001676138,0.0003312156,0.0004148426,0.0004708711],"domain_scores_gemma":[0.9990208,0.000353098,0.00001830298,0.0001791054,0.0002596847,0.0001690195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004546627,0.0001857156,0.001291095,0.00001283937,0.00001294651,0.000001803439,0.0001269319,0.00001298314,0.8677033,0.0009018839,0.0292869,0.1004181],"study_design_scores_gemma":[0.0002923093,0.0003003944,0.0224346,0.0000114755,0.000008444375,0.00000750018,0.0002370192,0.001817265,0.01416094,0.001169784,0.9593906,0.0001696168],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861912,0.0003225465,0.00002800621,0.01003332,0.00006650447,0.0004743742,0.0002479459,0.00004804505,0.002588068],"genre_scores_gemma":[0.9868581,0.0002382641,0.007859851,0.0004120501,0.001460091,0.0001107366,0.0001638648,0.000002685643,0.002894387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9301037,"threshold_uncertainty_score":0.9994999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09619931702979753,"score_gpt":0.3434388580544716,"score_spread":0.2472395410246741,"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."}}