{"id":"W1516755352","doi":"10.11606/t.95.2009.tde-17092010-123112","title":"Abordagem algébrica para seleção de clones ótimos em projetos genomas e metagenomas","year":2009,"lang":"pt","type":"dissertation","venue":"","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Biology; Computational biology; Genetics","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":[0.003387461,0.0008972736,0.001237972,0.001518165,0.001316369,0.002179776,0.001077999,0.00100143,0.002875574],"category_scores_gemma":[0.006683813,0.0007828253,0.001424349,0.001559416,0.0006105158,0.0009798444,0.001660827,0.001843237,0.002508071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005336761,"about_ca_system_score_gemma":0.001075304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002581069,"about_ca_topic_score_gemma":0.005791904,"domain_scores_codex":[0.9977762,0.0005797637,0.0001958677,0.000571636,0.0005663886,0.000310074],"domain_scores_gemma":[0.9966295,0.00117211,0.000308376,0.0008247068,0.000826783,0.0002384025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009219093,0.0003825169,0.009738812,0.0005508005,0.0001113732,0.000499859,0.001099554,0.000864219,0.8593727,0.0007424929,0.001470182,0.1242456],"study_design_scores_gemma":[0.0003369878,0.00142015,0.03295104,0.0002471157,0.0009387298,0.002064214,0.001850648,0.01272271,0.9049783,0.001477274,0.04089051,0.000122337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6016794,0.002837588,0.3678437,0.00111994,0.0005470081,0.00377662,0.003007434,0.007297897,0.01189042],"genre_scores_gemma":[0.3884412,0.001870738,0.5832141,0.0007078374,0.00006893838,0.001966067,0.00633476,0.00153326,0.01586306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003387461,"threshold_uncertainty_score":0.01791483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02135678710676841,"score_gpt":0.3146402396818676,"score_spread":0.2932834525750991,"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."}}