{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003495577,0.00143625,0.001710947,0.002993487,0.001622815,0.006523757,0.003976239,0.002195883,0.202519],"category_scores_gemma":[0.0144887,0.0007187647,0.001641755,0.004681203,0.0007152559,0.003923941,0.003630046,0.003114733,0.2528776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001364578,"about_ca_system_score_gemma":0.003305717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002044326,"about_ca_topic_score_gemma":0.002163175,"domain_scores_codex":[0.9963715,0.0009945234,0.0003380164,0.000867105,0.001207926,0.0002208557],"domain_scores_gemma":[0.9939971,0.002000301,0.000295037,0.001397715,0.001908622,0.0004012522],"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":[0.0001518731,0.00004222923,0.0006365562,0.001149517,0.00008635877,0.0001301242,0.0001463853,0.001113069,0.001246289,0.01818069,0.7884947,0.1886223],"study_design_scores_gemma":[0.00003408617,0.00002118464,0.0003599165,0.0001948315,0.00002091819,0.0002122955,0.00005177134,0.002113161,0.0007822273,0.0252887,0.9708999,0.00002102467],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.002741989,0.01654191,0.2981324,0.01683762,0.005485495,0.001285995,0.2324812,0.1298006,0.2966927],"genre_scores_gemma":[0.02407647,0.01593845,0.3186778,0.0137781,0.002543885,0.002337804,0.4471526,0.02056219,0.1549327],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.202519,"threshold_uncertainty_score":0.6774937,"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."}}