{"id":"W2111734812","doi":"10.1093/nar/gkq916","title":"NIASGBdb: NIAS Genebank databases for genetic resources and plant disease information","year":2010,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Plant Pathogens and Fungal Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Institute on Aging","keywords":"Biology; Database; Genetic diversity; Genetic resources; Biotechnology; Computer science; Population","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002178779,0.002807697,0.003341242,0.01021135,0.001785262,0.004368662,0.00519121,0.001982199,0.04133539],"category_scores_gemma":[0.004742116,0.001187186,0.001177085,0.02307629,0.0004842487,0.004592734,0.003080245,0.002654094,0.06187075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00207776,"about_ca_system_score_gemma":0.005692821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01284282,"about_ca_topic_score_gemma":0.01023419,"domain_scores_codex":[0.9984462,0.0001829253,0.0005135099,0.000385974,0.0003231844,0.0001483376],"domain_scores_gemma":[0.997154,0.0003774698,0.0006072309,0.0004703748,0.0008281329,0.0005627343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009026959,0.000195,0.001923131,0.00409265,0.0001565186,0.0002091177,0.0003229164,0.0005349464,0.00982221,0.006381273,0.9408681,0.03459144],"study_design_scores_gemma":[0.0001979884,0.00002974575,0.004141325,0.0004001037,0.0001007611,0.0001566949,0.0001352642,0.001162115,0.002274721,0.003125045,0.9881975,0.00007875095],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001575448,0.001592771,0.006073917,0.0003381898,0.0001435285,0.000232479,0.9691179,0.01325457,0.007671244],"genre_scores_gemma":[0.0009210538,0.0004314429,0.006991041,0.00009298618,0.00001711037,0.0001969261,0.9896235,0.000600827,0.0011251],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04133539,"threshold_uncertainty_score":0.1382807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02930513850579531,"score_gpt":0.3023474805378035,"score_spread":0.2730423420320082,"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."}}