{"id":"W4403208474","doi":"10.1186/s40246-024-00679-5","title":"Leveraging large-scale datasets and single cell omics data to develop a polygenic score for cisplatin-induced ototoxicity","year":2024,"lang":"en","type":"article","venue":"Human Genomics","topic":"Hearing, Cochlea, Tinnitus, Genetics","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Institute in Oncology and Hematology; Children's Hospital Research Institute of Manitoba; Sunnybrook Hospital; CancerCare Manitoba; Research Manitoba; University of Manitoba","funders":"Canadian Institutes of Health Research; Children's Hospital Research Institute of Manitoba; Research Manitoba; CancerCare Manitoba Foundation; Health Sciences Centre Research Foundation","keywords":"Genome-wide association study; Biology; Ototoxicity; Cohort; Human genetics; Single-nucleotide polymorphism; Hearing loss; Computational biology; Genetic association; Cisplatin; Oncology; Bioinformatics; Genetics; Medicine; Internal medicine; Gene; Genotype; Audiology; Chemotherapy","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":[0.003539411,0.0009922076,0.0008012556,0.002772731,0.0005750401,0.001451848,0.0006112739,0.0005386236,0.002160273],"category_scores_gemma":[0.005617042,0.00025261,0.001642549,0.002483919,0.0003886172,0.000402281,0.001809224,0.0008427717,0.0003729879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004255541,"about_ca_system_score_gemma":0.000981028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004059737,"about_ca_topic_score_gemma":0.007419764,"domain_scores_codex":[0.9984815,0.0004551376,0.0001531055,0.0005337736,0.0002731338,0.0001034659],"domain_scores_gemma":[0.9964733,0.001824726,0.0007062145,0.0004004161,0.000355666,0.000239778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006481498,0.0001497286,0.8587897,0.0006175921,0.004025112,0.0007351612,0.0002076534,0.02172446,0.05128463,0.001725886,0.003098144,0.05699392],"study_design_scores_gemma":[0.0001273922,0.0005276757,0.8861487,0.0001614265,0.002487843,0.001015272,0.0002587221,0.07892279,0.009308495,0.01133318,0.009598086,0.0001104477],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8101042,0.00161108,0.1516639,0.000847206,0.00007923642,0.0002917927,0.03238432,0.0009877369,0.002030495],"genre_scores_gemma":[0.9163486,0.0005393841,0.05795725,0.0004177066,0.00005107651,0.0002935611,0.02359585,0.0001544477,0.000642151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004059737,"threshold_uncertainty_score":0.01871842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1830574980394769,"score_gpt":0.3332120689475547,"score_spread":0.1501545709080778,"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."}}