{"id":"W3123756752","doi":"10.20944/preprints201806.0191.v1","title":"Recent Developments in Using &lt;em&gt;Drosophila&lt;/em&gt; as a Model for Human Genetic Disease","year":2018,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Drosophila (subgenus); Human disease; Disease; Value (mathematics); Candidate gene; Biology; Gene; Genetics; Genetic model; Computational biology; Computer science; Medicine; Machine learning; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0006544329,0.0006649367,0.0008917045,0.0005675462,0.0002642988,0.00002155201,0.0007051078,0.005075914,0.0004186153],"category_scores_gemma":[0.0004832117,0.0006661807,0.0003003907,0.0002787009,0.0002808798,0.00005824321,0.001980661,0.003617395,0.0004694299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005220066,"about_ca_system_score_gemma":0.001034742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002393558,"about_ca_topic_score_gemma":0.00005379557,"domain_scores_codex":[0.9958856,0.00009167568,0.001051935,0.001698379,0.0004753933,0.0007970145],"domain_scores_gemma":[0.996988,0.00003569666,0.0004188883,0.001800514,0.0003402518,0.0004166686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007003349,0.008316585,0.710907,0.007030084,0.005031096,0.001815937,0.01311457,0.02831065,0.1905217,0.006529579,0.00117957,0.02023988],"study_design_scores_gemma":[0.008874566,0.0002444138,0.7646723,0.006173907,0.001927385,0.0001774897,0.0001191426,0.09982222,0.03134134,0.06792557,0.0157578,0.00296384],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897191,0.001327721,0.001393762,0.002495962,0.0007798048,0.002645069,0.00003559727,0.0002942741,0.001308722],"genre_scores_gemma":[0.9881456,0.002714204,0.005394728,0.0008092322,0.00024693,0.0004093194,0.0001819831,0.0001253002,0.001972684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1591803,"threshold_uncertainty_score":0.999579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1185401268667017,"score_gpt":0.3562222976397899,"score_spread":0.2376821707730882,"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."}}