{"id":"W2789250540","doi":"10.1093/femsle/fny069","title":"Community-led comparative genomic and phenotypic analysis of the aquaculture pathogen Pseudomonas baetica a390T sequenced by Ion semiconductor and Nanopore technologies","year":2018,"lang":"en","type":"article","venue":"FEMS Microbiology Letters","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Fundação para a Ciência e a Tecnologia; Directorate for Biological Sciences; Industrial Biotechnology Innovation Centre; Vlaamse regering; Chief Scientist Office; Evelyn Trust; Biotechnology and Biological Sciences Research Council; Rosetrees Trust; Fonds Wetenschappelijk Onderzoek; University of Strathclyde","keywords":"Ion semiconductor sequencing; Biology; Genome; Phylogenetic tree; Strain (injury); Nanopore sequencing; Clade; Genetics; Evolutionary biology; DNA sequencing; Gene","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":[0.0003462445,0.0002986139,0.0003848333,0.0007898663,0.0004205666,0.0004163105,0.0002949276,0.0004700061,0.0006963374],"category_scores_gemma":[0.0006753455,0.0001703782,0.000485603,0.0009045515,0.0001940547,0.0002613582,0.0005830826,0.0004950454,0.000395976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002477631,"about_ca_system_score_gemma":0.0003783703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002852865,"about_ca_topic_score_gemma":0.003494886,"domain_scores_codex":[0.9996389,0.00004077989,0.00002044668,0.0001031362,0.0001414253,0.00005520319],"domain_scores_gemma":[0.9996372,0.00005943487,0.0000520722,0.00003848185,0.0001485117,0.00006427428],"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":[0.00007674572,0.00004285677,0.0009643814,0.0000376645,0.000007691759,0.00006966525,0.00008655473,0.00008844776,0.9970394,0.00003533134,0.00004089157,0.001510268],"study_design_scores_gemma":[0.0000958524,0.00135879,0.3350435,0.00005545702,0.0002060989,0.002568776,0.001914958,0.009949636,0.638483,0.0005469808,0.009699781,0.00007722152],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990488,0.0002435597,0.004467403,0.00006507173,0.00001867011,0.00007502572,0.003408579,0.00007978947,0.001154003],"genre_scores_gemma":[0.9663476,0.0004072177,0.021865,0.0001063092,0.00001459058,0.0001204087,0.00962033,0.00009052024,0.001428041],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002852865,"threshold_uncertainty_score":0.005672514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01154011335708956,"score_gpt":0.2290823874225693,"score_spread":0.2175422740654797,"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."}}