{"id":"W2919332642","doi":"","title":"Application of SMILES strings to identification of functional groups responsible for biological activity in medicinal compounds","year":2018,"lang":"en","type":"article","venue":"Amazonia Investiga","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Functional group; Identification (biology); Biological activity; Computer science; Biology; Chemistry; Ecology; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001569588,0.0000998668,0.0002034105,0.0002877022,0.0000548997,0.00002016746,0.0004398066,0.00006194932,0.000002402062],"category_scores_gemma":[0.0006354376,0.00009635671,0.00004766641,0.0008084695,0.0002710038,0.0002519088,0.000156522,0.00007001643,0.000006412202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006752955,"about_ca_system_score_gemma":0.0002108956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008823176,"about_ca_topic_score_gemma":0.00003708548,"domain_scores_codex":[0.9985802,0.0001812216,0.0004247319,0.0003738622,0.000287035,0.0001529054],"domain_scores_gemma":[0.9981917,0.0008611917,0.0002493405,0.0003353658,0.0002894793,0.00007293181],"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":[0.0002178471,0.0001596717,0.01488351,0.00003984696,0.00001345,2.408693e-7,0.0005619231,0.004769066,0.7001705,0.2602516,0.0002948061,0.01863755],"study_design_scores_gemma":[0.000324953,0.0003094464,0.6117674,0.00002617379,0.000004062309,0.000002709167,0.00001905518,0.1348075,0.1704683,0.08194941,0.0002197152,0.0001013148],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4981014,0.000007790956,0.5008963,0.0006303135,0.00009847111,0.0002119996,0.000008235177,0.00001675194,0.00002878537],"genre_scores_gemma":[0.9169214,0.000001022588,0.08276397,0.000132092,0.00007628751,0.00008127956,0.00001015214,0.000004711728,0.000009019979],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5968838,"threshold_uncertainty_score":0.3929313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0604074918752968,"score_gpt":0.3303570907803511,"score_spread":0.2699495989050543,"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."}}