{"id":"W2897681960","doi":"10.5808/gi.2018.16.3.44","title":"Antibacterial and Pharmacological Evaluation of Fluoroquinolones: A Chemoinformatics Approach","year":2018,"lang":"en","type":"article","venue":"Genomics & Informatics","topic":"Cancer therapeutics and mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Science and Engineering Research Board; University of Delhi; Department of Science and Technology, Ministry of Science and Technology, India; Department of Science and Technology, Republic of the Philippines; Department of Biotechnology, Ministry of Science and Technology, India","keywords":"Norfloxacin; Lomefloxacin; Ofloxacin; DNA gyrase; Enoxacin; Ciprofloxacin; Pharmacology; Chemistry; Antibacterial activity; Gatifloxacin; Antibiotics; Microbiology; Biology; Bacteria; Biochemistry; Escherichia coli","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":[0.0005966256,0.0001314764,0.0001599504,0.00004497867,0.00006892487,0.00002899912,0.0001520822,0.0001399957,0.00002555869],"category_scores_gemma":[0.00002132377,0.0001217957,0.00004617956,0.00005932634,0.0001559245,0.00001152901,0.0001493922,0.00005634522,0.000005836112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002784559,"about_ca_system_score_gemma":0.0001483423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001912756,"about_ca_topic_score_gemma":0.000001198324,"domain_scores_codex":[0.9990785,0.00002296482,0.0004207121,0.00009037671,0.000197812,0.0001896938],"domain_scores_gemma":[0.9992249,0.000004556085,0.0002281522,0.0002094763,0.0002722178,0.0000606737],"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":[0.0002297751,0.00008312053,0.00004577485,0.0001073177,0.0001989873,6.835347e-8,0.003393878,0.0001229349,0.9373437,0.0007114606,0.0004477711,0.05731522],"study_design_scores_gemma":[0.00301637,0.0009519918,0.0003097934,0.00001289151,0.0002953948,0.00005184161,0.00156617,0.06410656,0.8947685,0.0005078033,0.03403356,0.0003791011],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870579,0.0001324265,0.009336074,0.00001283301,0.0002372563,0.000347738,0.00004025721,0.000008311014,0.002827173],"genre_scores_gemma":[0.9833664,0.0003696214,0.0154656,0.0003803801,0.0002716573,0.00001502532,0.0001013787,0.00001168988,0.00001829957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06398363,"threshold_uncertainty_score":0.4966685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0278136537690907,"score_gpt":0.289365024118271,"score_spread":0.2615513703491803,"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."}}