{"id":"W2089145320","doi":"10.1006/gcen.2001.7659","title":"Development of a Retinoic Acid Receptor-Binding Assay with Rainbow Trout Tissue: Characterization of Retinoic Acid Binding, Receptor Tissue Distribution, and Developmental Changes","year":2001,"lang":"en","type":"article","venue":"General and Comparative Endocrinology","topic":"Retinoids in leukemia and cellular processes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Allergan","keywords":"Biology; Retinoic acid; Retinoid X receptor; Receptor; Nuclear receptor; Retinoid; Retinoic acid receptor; Tretinoin; Rainbow trout; Internal medicine; Kidney; Binding site; Endocrinology; Molecular biology; Biochemistry; Transcription factor; Gene; Fish <Actinopterygii>","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001394066,0.0002892603,0.0004274533,0.00007810533,0.0001860866,0.00001841683,0.0001532028,0.0001488603,0.00007260398],"category_scores_gemma":[0.00002981161,0.0002488485,0.0000224624,0.0001783134,0.0003356352,0.0000144358,0.000156553,0.0001205226,0.00000743401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004145206,"about_ca_system_score_gemma":0.000130825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000529481,"about_ca_topic_score_gemma":0.00002344713,"domain_scores_codex":[0.9984405,0.0001410802,0.0003964402,0.000491215,0.0001555452,0.0003751869],"domain_scores_gemma":[0.9992814,0.00001350825,0.0003114822,0.000138939,0.0001670729,0.00008757802],"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":[0.0002822051,0.00005151634,0.008121489,0.00006484057,0.0001005262,0.000003264897,0.0008071035,4.188865e-7,0.9830809,0.0001224099,0.0002044647,0.007160905],"study_design_scores_gemma":[0.0007529094,0.0005184376,0.003349586,0.00004662859,0.00002074797,0.00009316538,0.0004690688,0.000003449563,0.9127907,0.0000038696,0.08167766,0.0002737695],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964665,0.0007519701,0.001939173,0.0001178071,0.0001033405,0.0002719786,0.0000934351,0.0000155198,0.0002402854],"genre_scores_gemma":[0.9880095,0.0008633439,0.007062888,0.00002635975,0.0001101719,0.00007284486,0.00235713,0.0000159491,0.001481814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0814732,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02161885800871483,"score_gpt":0.2586236682619196,"score_spread":0.2370048102532047,"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."}}