{"id":"W4362523001","doi":"10.1038/s41467-023-37169-6","title":"Structural insights into the mechanism of leptin receptor activation","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"Regulation of Appetite and Obesity","field":"Neuroscience","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of General Medical Sciences; Canadian Institutes of Health Research; National Institute of Allergy and Infectious Diseases; Division of Intramural Research, National Institute of Allergy and Infectious Diseases; Howard Hughes Medical Institute; National Institutes of Health; National Science Foundation","keywords":"Mechanism (biology); Leptin; Receptor; Leptin receptor; Computational biology; Cell biology; Chemistry; Biology; Genetics; Endocrinology; Obesity; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001252153,0.0000672699,0.00007388878,0.00009615946,0.0005102882,0.00002330102,0.001003208,0.0001220155,0.00003049455],"category_scores_gemma":[0.0004983396,0.00004699449,0.00004572145,0.0008298574,0.0001514885,0.0001608436,0.0002947277,0.0004112761,0.00007288696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002277317,"about_ca_system_score_gemma":0.00002806847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001713266,"about_ca_topic_score_gemma":0.00006715576,"domain_scores_codex":[0.9992296,0.0001910866,0.0001555161,0.0001280604,0.0002122198,0.00008357342],"domain_scores_gemma":[0.9980745,0.0005756234,0.0001203815,0.001124808,0.00008212183,0.00002261007],"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":[0.000004681379,0.00001130813,0.00006999941,0.000003134176,0.000002559809,3.517891e-8,0.001652716,0.00002829861,0.5442845,0.4511472,0.001324868,0.001470653],"study_design_scores_gemma":[0.0001281196,0.0000184801,0.01255265,0.00001780839,0.000005051914,4.888978e-7,0.0002549988,0.004088844,0.8925092,0.02566851,0.06466603,0.00008983862],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839496,0.00008919068,0.00004951451,0.01237497,0.0001719529,0.0002077014,0.000003756044,0.0001166545,0.003036687],"genre_scores_gemma":[0.9982128,0.0003321901,0.0006028236,0.0004151779,0.00003202288,0.00001420792,0.00003377167,0.000007897699,0.0003491344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4254787,"threshold_uncertainty_score":0.3924776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03906236492787494,"score_gpt":0.3108397746299454,"score_spread":0.2717774097020704,"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."}}