{"id":"W2395907205","doi":"10.1186/s40246-016-0063-5","title":"Human genome meeting 2016","year":2016,"lang":"en","type":"article","venue":"Human Genomics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Université de Sherbrooke; McGill University; University of British Columbia","funders":"Nestec; Danone","keywords":"Human genetics; Genome Biology; Human genome; Biology; Computational biology; Genome; Genetics; Personal genomics; Genomics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001841951,0.001219116,0.001118395,0.002247209,0.001221095,0.003521385,0.001599767,0.002930734,0.253991],"category_scores_gemma":[0.002700548,0.0005357877,0.001067086,0.0021047,0.0003817336,0.0008557319,0.002419931,0.002360599,0.1785461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001154389,"about_ca_system_score_gemma":0.002482523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003892324,"about_ca_topic_score_gemma":0.006823144,"domain_scores_codex":[0.9991854,0.0001757258,0.00005136669,0.0002246962,0.000264873,0.0000979619],"domain_scores_gemma":[0.9990126,0.00009247676,0.00007099404,0.000169412,0.0003087914,0.0003456769],"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":[0.0001846556,0.000029673,0.0009764195,0.0003410607,0.00006236135,0.0002514611,0.00004748873,0.00009993811,0.002493127,0.002884827,0.8596444,0.1329846],"study_design_scores_gemma":[0.00002308772,0.00001258606,0.001211868,0.000159798,0.0000173758,0.000244561,0.00002272293,0.00008411548,0.0003237806,0.001128416,0.9967628,0.000009025147],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006305236,0.07378861,0.02477987,0.07966723,0.05814466,0.0007513493,0.2839821,0.009226819,0.4633541],"genre_scores_gemma":[0.02412066,0.03950225,0.02856844,0.01286868,0.008379381,0.000693344,0.4192452,0.001709978,0.4649121],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.253991,"threshold_uncertainty_score":0.8496847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01282574438570427,"score_gpt":0.2470131399698772,"score_spread":0.2341873955841729,"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."}}