{"id":"W4392288047","doi":"10.5530/pj.2024.16.8","title":"Predictive Simulation and Functional Insights of Serotonin Transporter: Ligand Interactions Explored through Database Analysis","year":2024,"lang":"en","type":"article","venue":"Pharmacognosy Journal","topic":"Receptor Mechanisms and Signaling","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Serotonin transporter; Serotonin Plasma Membrane Transport Proteins; Transporter; Paroxetine; Ligand (biochemistry); Chemistry; Serotonin; In silico; Hydrogen bond; Stereochemistry; Biochemistry; Receptor; Molecule","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":[0.0001382232,0.0001146886,0.0001396436,0.0001376876,0.0001058931,0.00005116442,0.00004989313,0.0000426306,0.0002926874],"category_scores_gemma":[0.00001083828,0.00009773643,0.0001563074,0.000205888,0.00003055228,0.00005208408,0.0000204466,0.0001772102,0.00000138582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001001976,"about_ca_system_score_gemma":0.00004948898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005445491,"about_ca_topic_score_gemma":0.000004422174,"domain_scores_codex":[0.999194,0.00005014841,0.0002738844,0.0002174728,0.000157048,0.0001074419],"domain_scores_gemma":[0.9996228,0.00003308809,0.00008273735,0.00007087917,0.0001125579,0.00007796934],"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":[0.0002109976,0.00005176456,0.0006983604,0.00002616165,0.001372825,0.00001432156,0.0006175393,0.0313601,0.9642485,0.00003148673,0.0002438132,0.001124067],"study_design_scores_gemma":[0.0005673019,0.0001409854,0.0005549572,0.00006589112,0.0009936501,0.00005613152,0.0002362618,0.07863379,0.9081514,0.0002430262,0.01021306,0.0001435623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7314733,0.002245524,0.2656913,0.00003762358,0.0003495876,0.00007651036,0.00005754398,0.000008294843,0.00006040389],"genre_scores_gemma":[0.9975336,0.001093218,0.0006270806,0.00004944098,0.0004290346,0.000006374643,0.0001891385,0.00001345933,0.00005870933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2660603,"threshold_uncertainty_score":0.3985576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03564194442728115,"score_gpt":0.32635496690729,"score_spread":0.2907130224800089,"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."}}