{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001648088,0.0008416998,0.0006924123,0.004044953,0.0003793381,0.001051084,0.0006457142,0.00043816,0.008043777],"category_scores_gemma":[0.0081909,0.0002551283,0.0008202756,0.002810978,0.0003163654,0.0008388287,0.001045757,0.0004826424,0.001783502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003377881,"about_ca_system_score_gemma":0.0008328243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003493945,"about_ca_topic_score_gemma":0.000418825,"domain_scores_codex":[0.9988973,0.0004065021,0.0001726763,0.0001789672,0.0002892922,0.00005526017],"domain_scores_gemma":[0.9955851,0.002911629,0.0005722031,0.0003301768,0.0004759777,0.0001249501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005195234,0.0008597844,0.07321116,0.003531743,0.0004849535,0.001711451,0.001519903,0.0317608,0.06000537,0.02921592,0.03214633,0.7603573],"study_design_scores_gemma":[0.0005888729,0.003153645,0.06529447,0.000702075,0.0004588584,0.003484177,0.001229145,0.5844133,0.1297407,0.05629201,0.1543518,0.0002909015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2705254,0.001059001,0.6431225,0.0005238143,0.000142503,0.0007949594,0.03059967,0.04281751,0.01041468],"genre_scores_gemma":[0.3762664,0.0005148542,0.5938717,0.0001647827,0.00006202419,0.00131517,0.02387369,0.001346631,0.002584796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008043777,"threshold_uncertainty_score":0.02690905,"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."}}