{"id":"W4412825375","doi":"10.1101/2025.07.28.667339","title":"<i>ADCY3</i> Ser107Pro links difficulty awakening in the morning to adiposity through circadian regulation of adipose thermogenesis","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Circadian rhythm and melatonin","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; National Human Genome Research Institute; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; German Network for Bioinformatics Infrastructure; Deutscher Akademischer Austauschdienst; Alexander von Humboldt-Stiftung","keywords":"Morning; Circadian rhythm; Thermogenesis; Adipose tissue; Endocrinology; Internal medicine; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003249447,0.0004343958,0.000319672,0.0002051782,0.0001890911,0.0003715862,0.0002296724,0.0004222399,0.006570914],"category_scores_gemma":[0.0007141666,0.0001090202,0.0004610109,0.0002318309,0.0003633802,0.0001275638,0.0003457417,0.0005669,0.0004140729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001618139,"about_ca_system_score_gemma":0.0002088048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002969925,"about_ca_topic_score_gemma":0.002610712,"domain_scores_codex":[0.9998417,0.00003823735,0.00001417457,0.00006035036,0.00002727397,0.00001823436],"domain_scores_gemma":[0.9996284,0.00009975216,0.0001699856,0.00004082514,0.00001612311,0.00004496543],"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":[0.01019542,0.0002114644,0.3986397,0.0008867998,0.001894066,0.009939478,0.0007632014,0.004300004,0.496222,0.003223332,0.01604087,0.05768377],"study_design_scores_gemma":[0.0002794799,0.0003425865,0.9384046,0.0001185787,0.0005346034,0.006128437,0.0002746504,0.005317253,0.03708383,0.003934309,0.007537725,0.00004402334],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902768,0.0007281172,0.00394496,0.0008160889,0.0001218586,0.000009601728,0.002424577,0.0001634644,0.001514607],"genre_scores_gemma":[0.9953849,0.0002711685,0.001214473,0.0002843473,0.00007763369,0.00001551753,0.001278489,0.00007427325,0.00139938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006570914,"threshold_uncertainty_score":0.02198189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02359142810912352,"score_gpt":0.2406837861599142,"score_spread":0.2170923580507907,"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."}}