{"id":"W2872913067","doi":"10.1002/9781118445112.stat07989","title":"Big Data in Biosciences","year":2017,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Forest Service; Natural Resources Canada; University of Toronto; Western University","funders":"","keywords":"Big data; Data science; Computer science; Context (archaeology); Analytics; Wearable computer; Geography; Data mining","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":[0.01433497,0.0009442092,0.001302387,0.00967732,0.002002026,0.01441827,0.001985339,0.004132176,0.0447132],"category_scores_gemma":[0.04246864,0.0006355289,0.0009820276,0.01901042,0.0051384,0.01359508,0.007553058,0.006711886,0.02179156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004049172,"about_ca_system_score_gemma":0.008647811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004362233,"about_ca_topic_score_gemma":0.00358704,"domain_scores_codex":[0.9900362,0.004476286,0.0007055911,0.000795007,0.003595736,0.0003911882],"domain_scores_gemma":[0.9524632,0.03002763,0.001733931,0.006048614,0.007110477,0.00261621],"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":[0.00003343921,0.00001765807,0.001293351,0.001020179,0.00004293254,0.0001002708,0.0003505488,0.0006124381,0.0001376325,0.2526947,0.5966031,0.1470937],"study_design_scores_gemma":[0.000005972302,0.000006666576,0.0006464728,0.001375801,0.000007843513,0.00007689837,0.0002435342,0.0003764788,0.00009177131,0.1527117,0.8444387,0.0000181607],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.002223643,0.1884452,0.05936213,0.3961398,0.02997274,0.0002893045,0.03164335,0.005570896,0.286353],"genre_scores_gemma":[0.0780899,0.4389422,0.1230258,0.1314839,0.05380812,0.00121368,0.04829679,0.006343627,0.118796],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0447132,"threshold_uncertainty_score":0.1495805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1105974680227034,"score_gpt":0.3778925562011252,"score_spread":0.2672950881784218,"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."}}