{"id":"W4386799977","doi":"10.1038/s41598-023-42581-5","title":"Unraveling the link between PTBP1 and severe asthma through machine learning and association rule mining method","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute for Medical Research Development","keywords":"Asthma; Candidate gene; Gene; Single-nucleotide polymorphism; Disease; Medicine; Bioinformatics; Genetic association; Biology; Genotype; Immunology; Genetics; Internal medicine","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":[0.001466237,0.000485806,0.0007546504,0.001954562,0.0002821849,0.0008583901,0.0006147601,0.0005373965,0.0009642439],"category_scores_gemma":[0.002812264,0.0002192053,0.0008478117,0.001364312,0.0002384301,0.0005206103,0.0003829453,0.0009547134,0.0003491992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002520615,"about_ca_system_score_gemma":0.0007156289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001766666,"about_ca_topic_score_gemma":0.001630893,"domain_scores_codex":[0.9994711,0.0001104319,0.00007495177,0.0001656408,0.0001175802,0.00006031137],"domain_scores_gemma":[0.9988398,0.0006662008,0.0002040421,0.00006653123,0.0001702902,0.00005313718],"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":[0.000875947,0.0006661896,0.6187537,0.0005241244,0.0008422912,0.002475851,0.0002144487,0.02285457,0.03392559,0.001653113,0.002729472,0.3144847],"study_design_scores_gemma":[0.0001047549,0.0004389023,0.2426183,0.0001943091,0.001018915,0.004758418,0.0003599573,0.7168476,0.01854861,0.009192565,0.005839679,0.0000779023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7798172,0.005581662,0.2080904,0.001231701,0.0001321705,0.0001801636,0.002248467,0.0007229244,0.001995331],"genre_scores_gemma":[0.9263843,0.001239075,0.06976643,0.0001495775,0.00007876033,0.0001021082,0.00167556,0.00001671466,0.0005873673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001954562,"threshold_uncertainty_score":0.007754326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01705053938468376,"score_gpt":0.3119617670226454,"score_spread":0.2949112276379617,"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."}}