{"id":"W2309916540","doi":"10.1038/nbt.3343","title":"Affinity regression predicts the recognition code of nucleic acid–binding proteins","year":2015,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Cancer Institute; National Human Genome Research Institute; National Institutes of Health","keywords":"Nucleic acid; Computational biology; Regression; DNA-binding protein; Chemistry; Biochemistry; Biology; Gene; Mathematics; Transcription factor; Statistics","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":[0.0004265576,0.0001153356,0.0001303941,0.00009186853,0.00008386339,0.000009595923,0.0003697949,0.001195211,0.000006396072],"category_scores_gemma":[0.001107617,0.00007435869,0.00005345163,0.0002128502,0.000214588,0.000004293557,0.0002272401,0.0006951615,0.00001311752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002242988,"about_ca_system_score_gemma":0.0001032865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001333695,"about_ca_topic_score_gemma":0.00005717673,"domain_scores_codex":[0.9990438,0.00008212074,0.0001547558,0.0002717452,0.0001948933,0.000252675],"domain_scores_gemma":[0.9992153,0.00001055496,0.0001136814,0.0004451101,0.0001475236,0.00006780524],"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":[0.0001480677,0.00003657942,0.0002720063,0.00001313174,0.00002231776,0.000003848875,0.00001612532,9.8345e-7,0.9861717,0.0001738599,0.004158954,0.008982383],"study_design_scores_gemma":[0.0004671714,0.0004778813,0.0001780845,0.00004010428,0.000007520815,0.00002756537,0.0001366106,0.00006247911,0.9805035,0.0003034314,0.01770906,0.00008659255],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994811,0.001476035,0.0002740406,0.002434626,0.0001441905,0.0003174678,0.00004078475,0.00004280325,0.0004590709],"genre_scores_gemma":[0.9977777,0.0002137853,0.001418099,0.0001178216,0.0001156696,0.00002181267,0.00008278339,0.00001515041,0.0002371895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0135501,"threshold_uncertainty_score":0.9218559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0230579605256964,"score_gpt":0.2879165533740584,"score_spread":0.2648585928483619,"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."}}