{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003792504,0.0005036955,0.0006175799,0.004830375,0.001128353,0.0008254801,0.0004857381,0.0004045524,0.004235942],"category_scores_gemma":[0.001035547,0.0002354746,0.0008831902,0.003909335,0.000292726,0.0006206435,0.0006247361,0.0004972573,0.0008069621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005304163,"about_ca_system_score_gemma":0.0006216318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00356024,"about_ca_topic_score_gemma":0.007705821,"domain_scores_codex":[0.9996468,0.00003666386,0.000028701,0.0001449603,0.00009388697,0.00004892645],"domain_scores_gemma":[0.9996521,0.0001019866,0.00008809136,0.00002561728,0.00007089027,0.00006123619],"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":[0.001348847,0.0002618675,0.03626886,0.002931973,0.0004339041,0.001245237,0.002460155,0.001915364,0.84562,0.002325261,0.001864299,0.1033243],"study_design_scores_gemma":[0.0001044323,0.0009875206,0.7379226,0.0004653741,0.001179273,0.002782698,0.003040536,0.02014124,0.1188695,0.003350471,0.1109467,0.0002096465],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9225647,0.006426446,0.02891565,0.0003407012,0.0001799478,0.0002881128,0.02376726,0.001390799,0.01612633],"genre_scores_gemma":[0.8542389,0.002556502,0.0887832,0.000228102,0.00009288454,0.0005291243,0.04911119,0.0003332791,0.004126769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004830375,"threshold_uncertainty_score":0.01417065,"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."}}