{"id":"W4415334592","doi":"10.48550/arxiv.2503.02245","title":"Identification of Genetic Factors Associated with Corpus Callosum Morphology: Conditional Strong Independence Screening for Non-Euclidean Responses","year":2025,"lang":"en","type":"preprint","venue":"University of Birmingham Research Portal (University of Birmingham)","topic":"Plant Virus Research Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; Genentech; IXICO; National Natural Science Foundation of China; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Corpus callosum; Identification (biology); Metric (unit); Independence (probability theory); Conditional independence; Conditional random field; Genetic variants; Key (lock)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005467052,0.0007697234,0.0009871997,0.001285385,0.0006091453,0.000844533,0.001502017,0.0008752367,0.002403151],"category_scores_gemma":[0.02146122,0.0003268727,0.001479643,0.001051937,0.001231244,0.0007174836,0.001693225,0.001238495,0.0003471864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005104836,"about_ca_system_score_gemma":0.00191848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005033693,"about_ca_topic_score_gemma":0.005917472,"domain_scores_codex":[0.9980503,0.001136185,0.00006606877,0.0003484949,0.0002382479,0.0001608229],"domain_scores_gemma":[0.977835,0.01822494,0.001344127,0.001105077,0.0007377646,0.0007530961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001992189,0.0007488141,0.1550386,0.0004244966,0.001314486,0.002236177,0.0005643377,0.4892274,0.06217785,0.03983432,0.005944805,0.2404965],"study_design_scores_gemma":[0.00003767812,0.00009193446,0.01524922,0.00001378974,0.0000585245,0.0001685276,0.00004052775,0.9703043,0.004149474,0.009414067,0.0004297201,0.00004229374],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.292971,0.0001502646,0.7039286,0.0004398445,0.00002454328,0.0001018076,0.0005930287,0.0007765151,0.001014364],"genre_scores_gemma":[0.8252074,0.0001239728,0.1701592,0.0001933274,0.00004346186,0.0001817921,0.001835735,0.0001503233,0.002104637],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005467052,"threshold_uncertainty_score":0.0289129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1037439575252978,"score_gpt":0.305875604929794,"score_spread":0.2021316474044962,"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."}}