{"id":"W4411158875","doi":"10.1101/2025.06.08.653722","title":"RetiGene, a comprehensive gene atlas for inherited retinal diseases (IRDs)","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Children's Hospital; McGill Genome Centre; McGill University Health Centre","funders":"Instituto de Salud Carlos III; Fonds de Recherche du Québec - Santé; Vlaamse regering; Generalitat Valenciana; Fonds Wetenschappelijk Onderzoek; Fondazione Telethon; Bijzonder Onderzoeksfonds UGent; National Institutes of Health; Foundation Fighting Blindness; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Leids Universitair Medisch Centrum; Universiteit Gent; European Regional Development Fund; Fondation de l'Hôpital de Montréal pour enfants; European Commission; Fight for Sight UK; Children's Hospital Foundation; Canadian Institutes of Health Research; National Science Foundation","keywords":"Computational biology; Gene; Biology; Candidate gene; Disease; Genetics; Medicine","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":[0.001371949,0.001401825,0.001071763,0.005166731,0.0008741848,0.001845999,0.00191304,0.00115615,0.008244987],"category_scores_gemma":[0.002404924,0.0006173733,0.0009422083,0.005167875,0.0004787077,0.001023871,0.001982057,0.001241882,0.007283921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009482896,"about_ca_system_score_gemma":0.002890052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005443076,"about_ca_topic_score_gemma":0.01093203,"domain_scores_codex":[0.9990074,0.0001151727,0.0001002588,0.0003408588,0.0003519763,0.00008428135],"domain_scores_gemma":[0.9988331,0.000361369,0.0002197702,0.0002813022,0.0001665647,0.0001378033],"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":[0.001463132,0.0001114471,0.02667971,0.007515202,0.001064942,0.002826538,0.001326268,0.009607846,0.1973568,0.03376509,0.5604895,0.1577935],"study_design_scores_gemma":[0.0002017023,0.0001281951,0.03330358,0.0004295746,0.0004965259,0.003059957,0.0001978241,0.006986206,0.02765801,0.01613781,0.9112688,0.0001319232],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02729346,0.005733374,0.08569834,0.0005365573,0.0003460118,0.0001573154,0.8267137,0.03813526,0.01538593],"genre_scores_gemma":[0.03761334,0.003547095,0.1063751,0.0004459302,0.00008696216,0.0004056658,0.8416502,0.004398667,0.005477098],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008244987,"threshold_uncertainty_score":0.02758223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01654046446744615,"score_gpt":0.2333744745929247,"score_spread":0.2168340101254785,"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."}}