{"id":"W2774801279","doi":"10.1038/npp.2017.197","title":"The Promise of Genome Editing for Modeling Psychiatric Disorders","year":2017,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health","keywords":"Genome editing; Psychology; Psychiatry; MEDLINE; Computational biology; Genome; Genetics; Biology; Gene","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":[0.0007062709,0.0005972913,0.0005772301,0.0003963819,0.0003760942,0.001397779,0.0008777534,0.001263104,0.002440038],"category_scores_gemma":[0.0006310933,0.0002146086,0.0005358487,0.0001897977,0.00118599,0.001023159,0.000695146,0.002519372,0.0003436174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005699364,"about_ca_system_score_gemma":0.0005872225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008073847,"about_ca_topic_score_gemma":0.001014529,"domain_scores_codex":[0.9997919,0.0000692165,0.0000100611,0.00004268394,0.00005510822,0.00003111145],"domain_scores_gemma":[0.9997179,0.0001343967,0.00003347549,0.00004973347,0.00001954672,0.00004486621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006752374,0.0002404507,0.001899913,0.0006480601,0.0002024089,0.00099681,0.0001900798,0.01257825,0.6986366,0.1727416,0.007367121,0.1038235],"study_design_scores_gemma":[0.0003406196,0.001474377,0.005291229,0.0003053792,0.0003975069,0.003975658,0.0003904118,0.0520974,0.4602803,0.214563,0.2606787,0.0002054365],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3289329,0.0555902,0.5103835,0.0420875,0.003727111,0.0003083755,0.002552247,0.003343103,0.05307519],"genre_scores_gemma":[0.8599115,0.0335743,0.09492011,0.002563885,0.0004559781,0.0001368428,0.0007220777,0.0002020754,0.00751326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002440038,"threshold_uncertainty_score":0.008162737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01063300954863203,"score_gpt":0.3362518035241658,"score_spread":0.3256187939755337,"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."}}