{"id":"W4413128311","doi":"10.1101/2025.08.11.669561","title":"Looking Across Protein Domains to Identify Driver Mutations in Cancer","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Queen's University; Canada Research Chairs; Government of Ontario","keywords":"Cancer; Genetics; Biology; Computational biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001205921,0.000681298,0.0006473097,0.0035307,0.0003654569,0.0008230653,0.0003646111,0.0005809906,0.0006628304],"category_scores_gemma":[0.002441074,0.0001539953,0.0005914493,0.002042776,0.0002623068,0.000542364,0.0006388297,0.0004608624,0.0003336666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004818198,"about_ca_system_score_gemma":0.0003054404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001866368,"about_ca_topic_score_gemma":0.002320482,"domain_scores_codex":[0.9993265,0.0001668387,0.00004646727,0.0002279412,0.0001681209,0.0000641701],"domain_scores_gemma":[0.9986022,0.0007024533,0.0002628636,0.0001487747,0.0001774373,0.0001062546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001708723,0.0003600163,0.4376631,0.0008043076,0.001035249,0.0006936115,0.0001838525,0.2191707,0.1911082,0.00254523,0.003750644,0.1409763],"study_design_scores_gemma":[0.00002235229,0.0002185751,0.1435142,0.00003242638,0.0001817732,0.0006938742,0.0001483326,0.781539,0.0608764,0.009701521,0.003034932,0.00003666689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599359,0.001437869,0.03323287,0.0002188143,0.00003365484,0.00003324058,0.003163466,0.000902662,0.001041572],"genre_scores_gemma":[0.9730512,0.0002381997,0.02258402,0.0000443774,0.00001233375,0.00001357417,0.00365174,0.00004589718,0.0003586559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0035307,"threshold_uncertainty_score":0.006377578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009975181027848693,"score_gpt":0.2750460995825496,"score_spread":0.2650709185547009,"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."}}