{"id":"W2995236109","doi":"10.35691/jbm.9102.0102","title":"COMPARATIVE MITO-GENOMIC ANALYSIS OF DIFFERENT SPECIES OF GENUS CANIS BY USING DIFFERENT BIOINFORMATICS TOOLS","year":2019,"lang":"en","type":"article","venue":"Journal of Bioresource Management","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nutrasource","funders":"","keywords":"Genus; Biology; Computational biology; Evolutionary biology; Canis; Bioinformatics; Zoology; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.000130468,0.0001871972,0.0006598969,0.0002391898,0.00003480466,0.00001941763,0.0002778703,0.00005287512,0.00002743991],"category_scores_gemma":[0.000004260842,0.0001412097,0.0003624852,0.0001575909,0.00008004154,0.000001597388,0.0002418538,0.00005818746,7.889998e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004206815,"about_ca_system_score_gemma":0.0000125452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001150247,"about_ca_topic_score_gemma":0.000009339868,"domain_scores_codex":[0.99868,0.00004263864,0.000718703,0.0001339018,0.0002517648,0.0001730044],"domain_scores_gemma":[0.9986725,0.00002112087,0.0008530117,0.0002757685,0.0001187522,0.00005883668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001769053,0.0002518647,0.07779916,0.0001475273,0.008649965,0.000001677781,0.0008447955,0.008853779,0.9008057,0.00005140597,0.0007658807,0.001651309],"study_design_scores_gemma":[0.001907313,0.001713184,0.6657836,0.00009886928,0.004092583,0.000006028065,0.005361096,0.00546363,0.3041492,0.00001903234,0.01090333,0.0005021136],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969718,0.001058441,0.0009702494,0.00001865323,0.0001255951,0.0001907411,0.00009625896,5.963628e-7,0.0005676997],"genre_scores_gemma":[0.9981118,0.0005797378,0.000995641,0.00003099531,0.00005331315,0.000001154624,0.00002053482,0.000009144424,0.0001976308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5966566,"threshold_uncertainty_score":0.5758364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01955468617566964,"score_gpt":0.2384474784223617,"score_spread":0.2188927922466921,"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."}}