{"id":"W2763338947","doi":"10.24870/cjb.2017-a36","title":"Bioinformatics Database Tools in Analysis of Genetics of Neurodevelopmental Disorders","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Biotechnology","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computational biology; Statistical genetics; Genetics; Biology; Bioinformatics; Medical genetics; Genomics; Genome; Gene","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":[0.0004751271,0.00009627748,0.0003120505,0.0007063943,0.00009627613,0.00001275799,0.0006632798,0.0001388081,0.0002721922],"category_scores_gemma":[0.0003923636,0.00009828278,0.00006928237,0.0003803491,0.0008322109,0.0002446192,0.0001212565,0.0002719732,0.000008312309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002055368,"about_ca_system_score_gemma":0.0001828585,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006471224,"about_ca_topic_score_gemma":0.1149752,"domain_scores_codex":[0.9987968,0.00003281366,0.0005960219,0.000131993,0.0001575544,0.0002848688],"domain_scores_gemma":[0.9985691,0.00003833266,0.0007228994,0.0004726831,0.000008404787,0.0001886166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007232924,0.00003414688,0.8126304,0.00001703156,0.0001139826,0.00005028162,0.0005188988,0.001254075,0.007706401,0.00006429721,0.00006772378,0.1775355],"study_design_scores_gemma":[0.0003530155,0.0001042963,0.9809965,0.00003253872,0.00009974264,0.0000149124,0.0004775805,0.002052766,0.01325485,0.00008661178,0.002403891,0.0001232907],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969152,0.00006566133,0.001011308,0.001086221,0.0000700005,0.00009673252,0.00007903741,0.000001630613,0.0006742001],"genre_scores_gemma":[0.9951794,0.0003778328,0.004316404,0.0001050014,0.000003138832,6.854986e-7,0.000004931735,0.00000669983,0.000005948463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1774122,"threshold_uncertainty_score":0.9782598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115047001031644,"score_gpt":0.2533765475251533,"score_spread":0.2322260775148369,"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."}}