{"id":"W3135793359","doi":"10.1002/cjs.11595","title":"Statistical disease mapping for heterogeneous neuroimaging studies","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Disease; Neuroimaging; Inference; Statistical inference; Computer science; Statistical model; Machine learning; Artificial intelligence; Statistical hypothesis testing; Bayesian probability; Statistical analysis; Computational biology; Data mining; Data science; Medicine; Statistics; Psychology; Pathology; Neuroscience; Biology; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009114017,0.00007731705,0.0001146586,0.0000579361,0.0001016464,0.00003709272,0.00008432432,0.0000251034,0.0000247417],"category_scores_gemma":[0.0008620856,0.00007780846,0.00004295221,0.00004907116,0.00006863868,0.000002730756,0.00001140983,0.00005596882,0.000001082622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003521266,"about_ca_system_score_gemma":0.001341082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001044258,"about_ca_topic_score_gemma":0.0004622333,"domain_scores_codex":[0.9993417,0.00004064135,0.0002337914,0.0001313283,0.00007989199,0.0001726952],"domain_scores_gemma":[0.9987358,0.00003736608,0.0001129914,0.0001272024,0.0005630481,0.0004236129],"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":[0.0002448169,0.00008429777,0.0151924,0.0005111517,0.0006044027,0.002345744,0.0006874144,0.002321814,0.1785324,0.01119657,0.7134151,0.07486388],"study_design_scores_gemma":[0.001243527,0.0002729498,0.01317476,0.0001305063,0.0001542614,0.0003534539,0.001150528,0.0006918256,0.01895849,0.007755163,0.9557084,0.0004060896],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04384263,0.01121456,0.9405269,0.001623692,0.001241997,0.0001211566,0.001354761,0.000002547136,0.00007174424],"genre_scores_gemma":[0.9588092,0.0004657156,0.03875976,0.0008904868,0.0003743374,0.000006684145,0.0001582066,0.00002293764,0.0005126659],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9149666,"threshold_uncertainty_score":0.3172937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04750211142183648,"score_gpt":0.2982055008108877,"score_spread":0.2507033893890512,"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."}}