{"id":"W4411335038","doi":"10.1101/2025.06.13.659495","title":"Paralog interference preserves genetic redundancy","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; PROTEO","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Redundancy (engineering); Interference (communication); Computer science; Telecommunications","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":[0.000264499,0.0004713733,0.0004187677,0.0002583235,0.0002690896,0.0004409637,0.003080898,0.0003665914,0.00002091808],"category_scores_gemma":[0.00009219266,0.000516446,0.0001637323,0.0007838392,0.0001263295,0.0003030343,0.002569106,0.0007158158,0.00009297261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001733137,"about_ca_system_score_gemma":0.0009370476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007158671,"about_ca_topic_score_gemma":0.000002299618,"domain_scores_codex":[0.9970767,0.0001298503,0.0005604354,0.001381401,0.00032154,0.0005300138],"domain_scores_gemma":[0.9961229,0.0000893715,0.0003053911,0.002807945,0.0004493009,0.000225106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005029279,0.003045813,0.03610591,0.00370109,0.001361657,0.0003320381,0.0002081849,0.006994383,0.2586342,0.6573118,0.03191821,0.0003364299],"study_design_scores_gemma":[0.0009153518,0.0001692466,0.75421,0.002005215,0.0001762382,1.002205e-7,0.00000273354,0.1308267,0.07174327,0.001467287,0.03522678,0.003257028],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07028639,0.004556383,0.9182367,0.001930426,0.002097169,0.001149203,0.0002601204,0.001350875,0.00013274],"genre_scores_gemma":[0.7905924,0.0004046105,0.2078507,0.00016121,0.0002858994,0.0005964052,2.485574e-7,0.00002867468,0.00007989608],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.720306,"threshold_uncertainty_score":0.9997287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650423017213794,"score_gpt":0.2346478460983082,"score_spread":0.2181436159261703,"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."}}