{"id":"W3139227823","doi":"10.1101/2021.03.17.21253824","title":"ExPheWas: a browser for gene-based pheWAS associations","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"","keywords":"Biobank; Phenome; Gene; Phenotype; Bioinformatics; Medicine; Computational biology; Biology; Genetics","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":[0.003309928,0.002459157,0.001674121,0.003342764,0.0006972313,0.002983236,0.002450333,0.001586526,0.1734716],"category_scores_gemma":[0.01103389,0.001698167,0.002116658,0.003087473,0.000573676,0.002158675,0.003130164,0.002211542,0.0550505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009089559,"about_ca_system_score_gemma":0.002356961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004641776,"about_ca_topic_score_gemma":0.007761693,"domain_scores_codex":[0.9989421,0.0002802288,0.0001216999,0.0003045446,0.0002555048,0.00009592686],"domain_scores_gemma":[0.9940495,0.004389527,0.0002303879,0.0005926475,0.0004101469,0.0003278328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001614077,0.0001858126,0.01034964,0.002518622,0.000518223,0.001157835,0.0005160403,0.003826036,0.003978475,0.009386412,0.92336,0.04258874],"study_design_scores_gemma":[0.002079861,0.0001557382,0.0197309,0.0007536932,0.000325747,0.00204547,0.0003745058,0.03531737,0.008122598,0.06174293,0.8690495,0.0003016672],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.005322708,0.0007735452,0.08560269,0.001316539,0.0004921033,0.0003222178,0.5871176,0.3097617,0.009290787],"genre_scores_gemma":[0.05723104,0.001254566,0.1410815,0.001692366,0.0002960973,0.002113743,0.7118613,0.07098892,0.01348041],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1734716,"threshold_uncertainty_score":0.5803202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01862588159197133,"score_gpt":0.2580507869677008,"score_spread":0.2394249053757295,"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."}}