{"id":"W2040285328","doi":"10.1038/nbt.2685","title":"Identifying producers of antibacterial compounds by screening for antibiotic resistance","year":2013,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":218,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research","keywords":"Antibiotics; Glycopeptide; Antibiotic resistance; Biology; Bacteria; Computational biology; Drug discovery; Biotechnology; Microorganism; Microbiology; Biochemistry; Genetics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001794426,0.0001772882,0.0004369733,0.0002033313,0.00008368466,0.00002135229,0.0002126124,0.00107528,0.00004402837],"category_scores_gemma":[0.0005129767,0.0001384138,0.0001050341,0.0003544332,0.0002419601,0.00008927911,0.00006607158,0.0005904394,0.000007077852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003447055,"about_ca_system_score_gemma":0.00003193065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002696012,"about_ca_topic_score_gemma":0.000007230585,"domain_scores_codex":[0.9987375,0.00001801162,0.0003103486,0.0004787941,0.0001339,0.0003214054],"domain_scores_gemma":[0.9990682,0.00004693359,0.0001924998,0.0004262717,0.0002208937,0.00004517117],"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":[0.0001917527,0.00005713778,0.0001559718,0.0002952856,0.00006734671,0.000001434251,0.00001051469,1.457017e-8,0.9360853,0.0004734033,0.05640725,0.006254638],"study_design_scores_gemma":[0.0006966686,0.0001428305,0.001248487,0.0001957086,0.00006125653,0.00001926586,0.00003690852,0.000005313565,0.9443121,0.0001193909,0.05301904,0.0001430389],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9622928,0.003858882,0.0003236697,0.03092694,0.0007108978,0.001410839,0.00007823274,0.0002003708,0.000197363],"genre_scores_gemma":[0.9763819,0.000111276,0.02196015,0.000309064,0.0002099955,0.000001574457,0.00007070151,0.00002560705,0.0009297142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03061787,"threshold_uncertainty_score":0.8293542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01284866092681295,"score_gpt":0.2640239476946233,"score_spread":0.2511752867678104,"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."}}