{"id":"W4294243189","doi":"10.1111/mec.16679","title":"Detection of nucleotide modifications in bacteria and bacteriophages: Strengths and limitations of current technologies and software","year":2022,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Bacteriophages and microbial interactions","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Novo Nordisk Foundation Center for Basic Metabolic Research; Novo Nordisk Fonden; H. Lundbeck A/S; Human Frontier Science Program; Lundbeckfonden; Novo Nordisk; European Commission","keywords":"Biology; Software; Bacteria; Computational biology; Current (fluid); Evolutionary biology; Genetics; Programming language; Computer science; Engineering","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":[0.00005914421,0.00006441971,0.0001151191,0.00008683016,0.00008172617,0.000006548098,0.00005907512,0.00003316587,0.00007777908],"category_scores_gemma":[0.0001336792,0.00007273701,0.00001514556,0.0001303941,0.0002087218,0.00007131256,0.0002693474,0.0001112403,9.207739e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003954058,"about_ca_system_score_gemma":0.000005807143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009228353,"about_ca_topic_score_gemma":0.000754553,"domain_scores_codex":[0.9994746,0.00005517847,0.0001719712,0.0001718498,0.00003394242,0.00009249258],"domain_scores_gemma":[0.9996678,0.0001115025,0.00009146481,0.0001055472,0.000006439028,0.00001723358],"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":[0.000007990814,0.00007332638,0.004788787,0.00001103053,0.000005738843,0.000001682882,0.0002527979,0.0000688857,0.9130359,0.00006241276,0.000004616526,0.08168679],"study_design_scores_gemma":[0.0003189085,0.0002230967,0.9461051,0.000007310102,0.00002345501,0.00003464825,0.001034415,0.0002171266,0.04865471,0.0003765094,0.002897422,0.0001072548],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990311,0.0002119169,0.0003277939,0.0001346094,0.00006134178,0.0001505236,0.00003349921,0.00001586528,0.0000333387],"genre_scores_gemma":[0.99854,0.0003562869,0.001020253,0.00001191421,9.313409e-7,0.00004831866,0.000007160589,0.000005762621,0.000009372176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9413164,"threshold_uncertainty_score":0.2966129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246701763364133,"score_gpt":0.2392091143087741,"score_spread":0.2267420966751328,"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."}}