{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00557379,0.002024769,0.002630354,0.006682626,0.001249915,0.003685117,0.003348119,0.001505198,0.04010933],"category_scores_gemma":[0.01558995,0.001084116,0.002760195,0.009571447,0.0005304587,0.003011703,0.00343996,0.003006663,0.02825993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009427147,"about_ca_system_score_gemma":0.003490148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003377705,"about_ca_topic_score_gemma":0.003530385,"domain_scores_codex":[0.9961408,0.001109505,0.0008787528,0.0007291323,0.0008621063,0.0002797366],"domain_scores_gemma":[0.9908972,0.004977514,0.0009501645,0.001027627,0.001414309,0.0007331101],"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":[0.002156312,0.0003966144,0.009966902,0.01202491,0.00120923,0.001660349,0.0007755753,0.005161838,0.01188181,0.02506285,0.7372953,0.1924083],"study_design_scores_gemma":[0.0008209838,0.0002185756,0.01616141,0.00172799,0.0004874017,0.001651976,0.0005085443,0.02542882,0.01191895,0.06363522,0.8771659,0.0002742577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.00572615,0.005487625,0.1759122,0.002616435,0.0005773568,0.001401156,0.5937179,0.1957686,0.01879264],"genre_scores_gemma":[0.03482381,0.005808949,0.3341047,0.002103814,0.0002594042,0.00411314,0.5987626,0.01325736,0.006766136],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04010933,"threshold_uncertainty_score":0.1341791,"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."}}