{"id":"W1995261598","doi":"10.1016/j.jmgm.2007.04.012","title":"Exploring ligand recognition and ion flow in comparative models of the human GABA type A receptor","year":2007,"lang":"en","type":"article","venue":"Journal of Molecular Graphics and Modelling","topic":"Nicotinic Acetylcholine Receptors Study","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche; European Commission; Wellcome Trust","keywords":"GABAA receptor; Nicotinic acetylcholine receptor; Chemistry; Transmembrane domain; Receptor; Ion channel; Acetylcholine receptor; Nicotinic agonist; Torpedo; Muscarinic acetylcholine receptor M5; Biophysics; Biochemistry; Biology; Muscarinic acetylcholine receptor M3","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":[0.0006994981,0.0001106766,0.0002014166,0.0001141934,0.00005756603,0.00001160693,0.00008635089,0.00008108075,3.898166e-7],"category_scores_gemma":[0.0000196069,0.00008766053,0.0000793973,0.000155388,0.00006908799,0.00001637465,0.00006010006,0.0002178757,5.655313e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007463331,"about_ca_system_score_gemma":0.00002680962,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001368442,"about_ca_topic_score_gemma":0.00002397994,"domain_scores_codex":[0.999113,0.00005720842,0.0003964149,0.0001415967,0.0001583309,0.0001334719],"domain_scores_gemma":[0.9993564,0.00001651976,0.000253224,0.0001042341,0.0002125616,0.00005704294],"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":[0.0001642027,0.00009780302,0.0008974928,0.00002787892,0.00008368366,0.000001513319,0.0009783802,0.01967357,0.9767928,0.0002197786,0.00001162542,0.001051234],"study_design_scores_gemma":[0.00140242,0.0005253779,0.0002051489,0.0002958601,0.000064968,0.00004492702,0.0006561758,0.01365306,0.9800419,0.002648144,0.00024238,0.0002196602],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9657125,0.002008214,0.03198129,0.0000293794,0.0001033671,0.0001078637,0.000003112507,0.000001093769,0.00005311278],"genre_scores_gemma":[0.9942133,0.00305632,0.002611606,0.00003080311,0.00006724524,0.000001151764,0.00000438136,0.00001197046,0.000003164242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02936969,"threshold_uncertainty_score":0.3574693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1257640507498064,"score_gpt":0.2930328904834685,"score_spread":0.1672688397336621,"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."}}