{"id":"W2106330447","doi":"10.18433/j3jk5p","title":"Partial Least Square and Hierarchical Clustering in ADMET Modeling: Prediction of Blood – Brain Barrier Permeation of α-Adrenergic and Imidazoline Receptor Ligands","year":2013,"lang":"en","type":"article","venue":"Journal of Pharmacy & Pharmaceutical Sciences","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quantitative structure–activity relationship; Chemistry; Polar surface area; Capillary electrophoresis; Imidazoline receptor; Molecular descriptor; Chromatography; Molecule; Stereochemistry; Pharmacology; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002075128,0.0001436711,0.0003089648,0.0003617254,0.00008846653,0.0001050962,0.0004182743,0.00003740044,0.00005166716],"category_scores_gemma":[0.0002834259,0.0001157611,0.00007475886,0.0005934051,0.000350417,0.001443794,0.00024588,0.0002900284,4.271128e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001800819,"about_ca_system_score_gemma":0.0001938662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000381277,"about_ca_topic_score_gemma":0.000002170759,"domain_scores_codex":[0.9976381,0.0002814351,0.0008451839,0.0002816364,0.0007005498,0.0002530945],"domain_scores_gemma":[0.9986482,0.0004799775,0.0002924269,0.00008011139,0.0002268674,0.0002723821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002619722,0.0005027449,0.03430281,0.0001961181,0.00007559968,0.00001104594,0.002615817,0.3109874,0.5221226,0.003266474,0.00004350067,0.1256139],"study_design_scores_gemma":[0.001574793,0.0002153835,0.003496939,0.00008685738,0.00003340581,0.0000946209,0.00009068819,0.9570469,0.03608883,0.001078686,0.00009725348,0.0000956354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9142343,0.0007663604,0.08240175,0.002173261,0.0002324448,0.0001400869,0.000007202048,0.000008514506,0.00003606762],"genre_scores_gemma":[0.9835064,0.0002977328,0.01591232,0.0001270329,0.0001440042,0.000004149681,7.068591e-7,0.000005109168,0.000002567432],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6460595,"threshold_uncertainty_score":0.4720599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06179502809615169,"score_gpt":0.3634349185001014,"score_spread":0.3016398904039497,"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."}}