{"id":"W3207456493","doi":"10.1101/2021.10.13.464308","title":"PSEA: A phenotypic similarity ensemble approach for prioritizes candidate genes to aid mendelian disease diagnosis","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wycliffe College","funders":"","keywords":"Phenotype; Computational biology; Similarity (geometry); Genetics; Biology; Gene; Computer science; Artificial intelligence","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":[0.002059692,0.001270874,0.001248043,0.006025906,0.0006893513,0.001133685,0.0009849314,0.0007994156,0.004689154],"category_scores_gemma":[0.005172631,0.0002388535,0.001487279,0.00234585,0.0003157995,0.000801464,0.001876946,0.000779519,0.000918684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004670399,"about_ca_system_score_gemma":0.0009953257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00275618,"about_ca_topic_score_gemma":0.004314581,"domain_scores_codex":[0.9986211,0.0003301075,0.00009418448,0.000457815,0.000415637,0.00008119149],"domain_scores_gemma":[0.9984649,0.0007766543,0.0001606159,0.000179547,0.0003036734,0.0001146194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001051448,0.0005268616,0.05801103,0.0007270884,0.001713235,0.001144908,0.000292957,0.09120304,0.03541279,0.007153796,0.02698866,0.7757741],"study_design_scores_gemma":[0.0002100953,0.0004010043,0.02800779,0.0001172081,0.0008469085,0.001188303,0.0002268446,0.8878384,0.016841,0.04275947,0.02145187,0.0001111233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1052311,0.001819773,0.8670397,0.0008000446,0.0001735137,0.0003348372,0.01018412,0.0102669,0.004149945],"genre_scores_gemma":[0.5117722,0.000741618,0.4624052,0.0004604165,0.0002711292,0.0004888626,0.01976657,0.0009431174,0.003150856],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006025906,"threshold_uncertainty_score":0.01568681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0204828481194469,"score_gpt":0.2522513433204088,"score_spread":0.2317684952009619,"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."}}