{"id":"W2035276570","doi":"10.1002/chem.200400371","title":"Receptor‐Assisted Combinatorial Chemistry: Thermodynamics and Kinetics in Drug Discovery","year":2004,"lang":"en","type":"review","venue":"Chemistry - A European Journal","topic":"Chemical Synthesis and Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; McGill University","funders":"","keywords":"Drug discovery; Kinetics; Combinatorial chemistry; Chemistry; Receptor–ligand kinetics; Receptor; Computational biology; Computer science; Biochemical engineering; Thermodynamics; Biology; Biochemistry; Physics; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005900108,0.0006970738,0.001168388,0.00003855651,0.00009661166,0.0003007648,0.0007163845,0.0003270262,0.00009634959],"category_scores_gemma":[0.00020885,0.000602772,0.0006981306,0.0002254315,0.0002111157,0.00001074974,0.0004010881,0.001011049,0.000009345955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00021468,"about_ca_system_score_gemma":0.0002590053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002482939,"about_ca_topic_score_gemma":5.498819e-7,"domain_scores_codex":[0.9972101,0.0002661905,0.001001914,0.0007593862,0.0002777132,0.0004846498],"domain_scores_gemma":[0.9983125,0.00003780462,0.0006922545,0.0005629034,0.00007341397,0.0003210754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001063588,0.0008830637,0.00002168843,0.0157109,0.001059164,0.0004900313,0.00005487311,0.00001109375,0.5450466,0.000007684449,0.00188943,0.4347192],"study_design_scores_gemma":[0.001230825,0.00003743606,0.00001084176,0.007931196,0.0005933983,0.0008532939,0.00004703815,0.000008674755,0.006304947,0.00003458327,0.9818506,0.001097179],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02117554,0.9754851,0.00004896429,0.00003869237,0.0001858874,0.0001377669,0.00009683653,0.00001620231,0.002814968],"genre_scores_gemma":[0.008968708,0.9871652,0.0001368067,0.00001195285,0.001421463,0.000007742454,0.0005942594,0.0001593891,0.001534452],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9799612,"threshold_uncertainty_score":0.9996424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01116551175389059,"score_gpt":0.2428348872662636,"score_spread":0.231669375512373,"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."}}