{"id":"W4250603506","doi":"10.4018/978-1-5225-8903-7.ch003","title":"Bioinformatics","year":2019,"lang":"en","type":"book-chapter","venue":"Biotechnology","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Convergence (economics); Political science; Latin Americans; Data science; Biology; Biotechnology; Computer science; Economic growth; Economics; Law","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":[0.003710992,0.001452297,0.001642591,0.002993431,0.00161589,0.006274985,0.003822431,0.002030701,0.1942013],"category_scores_gemma":[0.01362535,0.0007192289,0.001604771,0.004548777,0.0007324388,0.00358656,0.00345206,0.002998658,0.2485545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001331867,"about_ca_system_score_gemma":0.003121487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001990641,"about_ca_topic_score_gemma":0.00220768,"domain_scores_codex":[0.9963812,0.00106743,0.0003275758,0.0008267189,0.001180674,0.0002164193],"domain_scores_gemma":[0.9942169,0.002032873,0.0002809034,0.001321729,0.001755442,0.000392183],"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":[0.0001651459,0.00004375443,0.0006426988,0.001140491,0.00008738323,0.0001322155,0.0001561432,0.001305919,0.001448609,0.01878924,0.7713258,0.2047625],"study_design_scores_gemma":[0.00003294593,0.00002212932,0.0003644007,0.0001758775,0.00002010559,0.0002129007,0.00005131157,0.002389045,0.0008516818,0.02614335,0.9697157,0.00002068786],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.002589252,0.01326121,0.3482134,0.01538498,0.004677209,0.001283092,0.2121841,0.1292669,0.27314],"genre_scores_gemma":[0.02295504,0.01305307,0.3759454,0.01169947,0.002229516,0.002271586,0.3980892,0.02009535,0.1536615],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1942013,"threshold_uncertainty_score":0.649668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554387657666277,"score_gpt":0.2510502464246959,"score_spread":0.2355063698480331,"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."}}