{"id":"W2950717017","doi":"10.1002/chin.200630233","title":"Can “Bacterial‐Metabolite‐Likeness” Model Improve Odds of “in Silico” Antibiotic Discovery?","year":2006,"lang":"en","type":"article","venue":"ChemInform","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chemistry; In silico; Metabolite; Odds; Antibiotics; Computational biology; Biochemistry; Computer science; Machine learning","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":[0.009419416,0.0007662399,0.001655554,0.001130211,0.0003558178,0.001260228,0.001306499,0.001517891,0.002949643],"category_scores_gemma":[0.03624847,0.0003366072,0.0008865501,0.0008164964,0.0006721151,0.002541051,0.0009229906,0.001273124,0.0007333642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006366528,"about_ca_system_score_gemma":0.0006970011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001490861,"about_ca_topic_score_gemma":0.002211334,"domain_scores_codex":[0.9970521,0.002184539,0.0000973437,0.0003472256,0.0002085941,0.0001102474],"domain_scores_gemma":[0.9787578,0.01797768,0.0009493843,0.001286277,0.0006375859,0.0003911905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006499752,0.000540009,0.05663949,0.0005340459,0.001316544,0.0003172368,0.00008862757,0.7693691,0.01056195,0.01180003,0.006107004,0.1362263],"study_design_scores_gemma":[0.0001250308,0.0002355609,0.00158967,0.00001415825,0.000114316,0.00006711103,0.00001231007,0.9852002,0.001900467,0.01028966,0.0004334797,0.00001799736],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6601077,0.002606056,0.3205014,0.005024799,0.0002646509,0.0001046536,0.001361947,0.003451852,0.006576959],"genre_scores_gemma":[0.9779754,0.0002614483,0.02006811,0.0004428535,0.00007812401,0.0000354385,0.0005963659,0.0001473748,0.0003949804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009419416,"threshold_uncertainty_score":0.04981518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007325828673323512,"score_gpt":0.2170423004900821,"score_spread":0.2097164718167585,"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."}}