{"id":"W2158752749","doi":"10.1186/1750-1172-7-39","title":"A generalizable pre-clinical research approach for orphan disease therapy","year":2012,"lang":"en","type":"review","venue":"Orphanet Journal of Rare Diseases","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Structural Genomics Consortium; Dalhousie University; University of Toronto; Université de Montréal; Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Institute of Genetics; FightSMA; Ontario Genomics Institute; National Institute of General Medical Sciences; Canadian Institutes of Health Research; Ontario Genomics","keywords":"Orphan drug; Disease; Toolbox; Repurposing; Medicine; Identification (biology); Computational biology; Bioinformatics; Biology; Computer science; Pathology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001356909,0.0006155702,0.001624579,0.0003150419,0.0002348369,0.0001513696,0.001168839,0.0004465162,0.0001217214],"category_scores_gemma":[0.0005086937,0.0004457272,0.002406906,0.0002447071,0.000267456,0.00001921122,0.0002442882,0.0004132227,0.00001203669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005383982,"about_ca_system_score_gemma":0.002256361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003544563,"about_ca_topic_score_gemma":6.854038e-7,"domain_scores_codex":[0.9955062,0.0009971075,0.001400427,0.0006740546,0.0005949244,0.0008272525],"domain_scores_gemma":[0.9956672,0.000210931,0.001026279,0.0008751606,0.0008005194,0.001419921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003070202,0.004652475,0.0009303517,0.01400466,0.003186198,0.0002359215,0.00002810591,0.00007132439,0.00002996791,0.0000855851,0.1622863,0.811419],"study_design_scores_gemma":[0.001028563,0.000703379,0.00009645398,0.0008600823,0.001628331,0.0001615481,0.00002002327,0.000007841175,0.000005920019,0.00006754632,0.9949021,0.0005181748],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005508926,0.9948685,0.0004836834,0.00001354304,0.0007976654,0.001407327,0.001810781,0.000009084982,0.0000585002],"genre_scores_gemma":[0.0006246114,0.987197,0.0011429,0.00009661707,0.005744474,0.0002483824,0.003464357,0.0001767733,0.001304866],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8326159,"threshold_uncertainty_score":0.9997994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1472749903912131,"score_gpt":0.4262006007581914,"score_spread":0.2789256103669784,"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."}}