{"id":"W2029864777","doi":"10.5598/imafungus.2013.04.02.17","title":"A without-prejudice list of generic names of fungi for protection under the International Code of Nomenclature for algae, fungi, and plants","year":2013,"lang":"en","type":"article","venue":"IMA Fungus","topic":"Plant Pathogens and Fungal Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Ministerio de Ciencia e Innovación","keywords":"Nomenclature; Prejudice (legal term); International Code of Zoological Nomenclature; Typification; Selection (genetic algorithm); Inclusion (mineral); Code (set theory); Biology; Computer science; Law; Political science; Set (abstract data type); Sociology; Ecology; Taxonomy (biology); Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007221258,0.00008617068,0.0001289309,0.00002749315,0.00003068254,0.000008553603,0.0001214519,0.00007665258,0.00001065119],"category_scores_gemma":[0.0000367566,0.00006271475,0.0000740649,0.00002856079,0.00006044179,0.000005313496,0.00004459466,0.00002694677,2.339836e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000424582,"about_ca_system_score_gemma":0.00003359519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003929593,"about_ca_topic_score_gemma":0.00002962406,"domain_scores_codex":[0.9994814,0.00001289438,0.0001707645,0.0001536562,0.00008088708,0.0001004053],"domain_scores_gemma":[0.9994894,0.00003162036,0.0001589765,0.0001316072,0.0001590676,0.00002931712],"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":[0.0003370839,0.00005195046,0.002902115,0.00009578017,0.0001182239,1.00073e-7,0.00002662786,0.00001838862,0.9917124,0.0001153942,0.001138608,0.00348334],"study_design_scores_gemma":[0.002005842,0.001092034,0.1046262,0.0001083106,0.0001607908,0.00003750347,0.000322814,0.004827246,0.8733156,0.00102837,0.01217095,0.0003044073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835483,0.00516847,0.006134118,0.00009197936,0.0001309724,0.0007715906,0.003973138,0.000003838943,0.000177613],"genre_scores_gemma":[0.9974775,0.0002688146,0.001500174,0.00007812856,0.0001027535,0.0001388248,0.0002118167,0.00001056182,0.0002114513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1183968,"threshold_uncertainty_score":0.2557434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597116178960646,"score_gpt":0.2417594792193365,"score_spread":0.2257883174297301,"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."}}