{"id":"W2773267230","doi":"10.3390/genes8120379","title":"The Genome of the Northern Sea Otter (Enhydra lutris kenyoni)","year":2017,"lang":"en","type":"article","venue":"Genes","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; Simon Fraser University; Vancouver Aquarium; University of British Columbia","funders":"Genome British Columbia; Genome Canada","keywords":"Otter; Mustelidae; Genome; Sequence assembly; Biology; Accession number (library science); Whole genome sequencing; Computational biology; DNA sequencing; Evolutionary biology; Transcriptome; Genetics; Gene; Fishery; Ecology; GenBank","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001645809,0.00006382063,0.00005095845,0.000007574806,0.0006468897,0.00007602311,0.0006638495,0.0000544068,0.00001422604],"category_scores_gemma":[0.00006407589,0.00003754676,0.00008478906,0.00002163038,0.0002091265,0.000002388213,0.0001330099,0.00003501008,0.00004440994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003644116,"about_ca_system_score_gemma":0.00003676568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002474755,"about_ca_topic_score_gemma":0.0002567936,"domain_scores_codex":[0.9994645,0.00003742815,0.0001458779,0.0001491198,0.00009827015,0.0001047647],"domain_scores_gemma":[0.9984657,0.000006497246,0.0001921712,0.001192275,0.0001230815,0.00002026313],"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":[0.00001389324,0.00002250829,0.03247975,0.000008066704,0.00004811157,8.668673e-8,0.00005893277,0.00001492973,0.9600735,0.0004087169,0.002229368,0.004642149],"study_design_scores_gemma":[0.0001081924,0.00001114705,0.1844715,0.00000195476,0.00000974001,0.000001827653,0.00003698387,0.00001008943,0.4412616,0.00004913804,0.3739764,0.00006135952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936922,0.001047836,0.0001743543,0.002581416,0.0004814572,0.0001333336,0.00002358636,0.000004526066,0.001861326],"genre_scores_gemma":[0.9908898,0.0002613105,0.00003040139,0.0001083275,0.000165078,0.00001655067,0.00001780118,0.000009452776,0.008501278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5188119,"threshold_uncertainty_score":0.4975418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01555004303137884,"score_gpt":0.2564695592327197,"score_spread":0.2409195162013409,"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."}}