{"id":"W4394484194","doi":"10.6084/m9.figshare.20416471","title":"Additional file 3 of Species-specific identification of Pseudomonas based on 16S–23S rRNA gene internal transcribed spacer (ITS) and its combined application with next-generation sequencing","year":2022,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Food Inspection Agency","funders":"","keywords":"Internal transcribed spacer; 23S ribosomal RNA; Identification (biology); Genetics; 16S ribosomal RNA; Computational biology; Biology; Gene; Ribosomal RNA; DNA sequencing; Pseudomonas; Bacteria; RNA; Botany","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00155156,0.001414925,0.001639953,0.002570186,0.001005704,0.001889777,0.002470226,0.001749497,0.4907528],"category_scores_gemma":[0.009624917,0.0005950913,0.0009685414,0.004576772,0.0004029822,0.001676716,0.001413432,0.001345221,0.103027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001209975,"about_ca_system_score_gemma":0.002168441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01223771,"about_ca_topic_score_gemma":0.02346931,"domain_scores_codex":[0.9992163,0.0001129165,0.0001173111,0.000290622,0.0001360068,0.0001267848],"domain_scores_gemma":[0.9953052,0.002778843,0.0003619308,0.000441358,0.0008420414,0.000270673],"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":[0.0002799179,0.00007574187,0.003029067,0.004042672,0.00007827461,0.0000727747,0.00006020537,0.0005367147,0.0004177099,0.0006348669,0.9869376,0.003834476],"study_design_scores_gemma":[0.002092364,0.00009737963,0.0172635,0.001834179,0.0001726738,0.0002100532,0.0002848249,0.0008834456,0.001013621,0.003978381,0.9720892,0.00008029642],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005525543,0.00000795816,0.00003432439,0.00001420536,0.000004152837,0.00000783442,0.9996884,0.00005929405,0.0001286718],"genre_scores_gemma":[0.0008244246,0.0000283254,0.0004834078,0.00006189337,0.0000064085,0.0001616908,0.9976762,0.00009930124,0.0006582885],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4907528,"threshold_uncertainty_score":0.7263793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04759705121592518,"score_gpt":0.248511089682527,"score_spread":0.2009140384666018,"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."}}