{"id":"W2536447134","doi":"10.4018/978-1-5225-1040-6.ch002","title":"Bioinformatics","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in bioinformatics and biomedical engineering book series","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Convergence (economics); Political science; Data science; Biology; Biotechnology; Computer science; Economic growth; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003934298,0.0006377466,0.0006065235,0.0004308114,0.00009243667,0.00008833068,0.000477254,0.0008642853,0.0001012804],"category_scores_gemma":[0.0002605453,0.0004811945,0.000155291,0.00007748124,0.0009353761,0.0001276975,0.0005391578,0.0004482397,0.00008142675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005921314,"about_ca_system_score_gemma":0.0001847844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.768097e-7,"about_ca_topic_score_gemma":0.000008664391,"domain_scores_codex":[0.9969842,0.000007208163,0.001231916,0.000331143,0.0007145029,0.0007310285],"domain_scores_gemma":[0.9985376,0.00006651643,0.0002847527,0.0005227821,0.000115462,0.0004728888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005508006,0.0001826307,0.00009082897,0.01147471,0.0006766961,0.0001086343,0.001114644,0.0001217171,0.003466068,0.104482,0.02133776,0.8563936],"study_design_scores_gemma":[0.0006649258,0.0006371941,0.00001214018,0.0007121218,0.00002077812,0.00007620692,0.00005279681,0.001693906,0.0004368701,0.000867046,0.9941127,0.0007133479],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.0003665182,0.0669935,0.04086582,0.002274259,0.003509678,0.002539484,0.001616497,0.0003485514,0.8814857],"genre_scores_gemma":[0.001157609,0.599916,0.06310049,0.001700976,0.001901542,0.0001024159,0.00164456,0.0003075385,0.3301689],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9727749,"threshold_uncertainty_score":0.999764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00631407355530728,"score_gpt":0.2326711911412413,"score_spread":0.226357117585934,"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."}}