{"id":"W4405528262","doi":"10.1002/sta4.70007","title":"A Corrected Score Function Framework for Modelling Circadian Gene Expression","year":2024,"lang":"en","type":"article","venue":"Stat","topic":"Circadian rhythm and melatonin","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Offset (computer science); Circadian rhythm; Function (biology); Regression; Expression (computer science); Sample (material); Computer science; Sample size determination; Statistics; Transcriptome; Regression analysis; Computational biology; Biology; Data mining; Gene expression; Mathematics; Gene; Genetics; Neuroscience","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":[0.00007697915,0.0001154434,0.0001000703,0.0001091324,0.0001596837,0.0001144644,0.00007678061,0.0001083078,0.00009476891],"category_scores_gemma":[0.0001287597,0.0001071692,0.0000778634,0.0002736786,0.00003374005,0.0001716101,0.00001909295,0.0002073336,0.0001454695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004574968,"about_ca_system_score_gemma":0.00006789991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004423342,"about_ca_topic_score_gemma":0.000001092348,"domain_scores_codex":[0.9989656,0.0000279293,0.0001351627,0.0004318881,0.0001449371,0.0002944806],"domain_scores_gemma":[0.9993472,0.000299703,0.00002568427,0.0001880985,0.00001991752,0.0001193735],"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":[0.0002047148,0.00004815628,0.0001637307,0.0002142558,0.00001013208,0.00009397959,0.002785785,0.007507564,0.7717206,0.1796221,0.004899335,0.03272955],"study_design_scores_gemma":[0.000219723,0.00009827116,0.00006940993,0.0003629348,0.00002310332,0.00003232755,0.00007047664,0.1547813,0.769635,0.03504612,0.03941121,0.0002501319],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2457428,0.0008855462,0.7496188,0.0001217598,0.002518362,0.0003080154,0.00006343166,0.0002689875,0.0004723088],"genre_scores_gemma":[0.9917633,0.00008637043,0.006077259,0.0003555864,0.0004180338,0.00007238491,0.00001457313,0.0000425356,0.001169935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7460205,"threshold_uncertainty_score":0.4370233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05786834505823168,"score_gpt":0.2837284382235453,"score_spread":0.2258600931653136,"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."}}