{"id":"W4316511288","doi":"10.1101/2023.01.13.523988","title":"Proofreading Is Too Noisy For Effective Ligand Discrimination","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Receptor Mechanisms and Signaling","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Proofreading; Ligand (biochemistry); Computer science; Noise (video); Computational biology; Biological system; Artificial intelligence; Biology; Receptor; Genetics; DNA; Polymerase","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":[0.007016741,0.001137865,0.002358529,0.0009069917,0.0007228161,0.004586811,0.001816007,0.002559318,0.005159055],"category_scores_gemma":[0.04431527,0.0008643756,0.001021086,0.0006938864,0.002589145,0.006027339,0.001778826,0.004464322,0.002501252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136624,"about_ca_system_score_gemma":0.001172509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001464802,"about_ca_topic_score_gemma":0.0001096738,"domain_scores_codex":[0.9936333,0.001559004,0.0006342568,0.001637077,0.001891938,0.0006444508],"domain_scores_gemma":[0.9519405,0.03443586,0.004126289,0.006537529,0.002023451,0.0009363765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001594437,0.0005193081,0.004586054,0.002084997,0.000181042,0.001495958,0.0004731329,0.03340805,0.7603573,0.1249742,0.002792384,0.06753318],"study_design_scores_gemma":[0.00009954397,0.0004218508,0.001653049,0.0001182613,0.00006442973,0.001592395,0.0001563999,0.1492472,0.7549573,0.08594249,0.005630527,0.0001166832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4484955,0.002971311,0.5323796,0.00243173,0.000791129,0.0001711186,0.0003634724,0.003168135,0.009227926],"genre_scores_gemma":[0.9374986,0.0007495236,0.05788661,0.0005801333,0.0001135827,0.0001073164,0.0003116539,0.0003693255,0.002383297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007016741,"threshold_uncertainty_score":0.03710848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622500011673573,"score_gpt":0.2454270848381534,"score_spread":0.2292020847214177,"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."}}