{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006422068,0.0002627659,0.0002041782,0.0004892235,0.0003491442,0.0003158402,0.0001676524,0.0002153887,0.0009633977],"category_scores_gemma":[0.000124795,0.0001331271,0.0002112121,0.0006427651,0.0001890563,0.0001591163,0.0002256787,0.0002441553,0.0005381269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003817946,"about_ca_system_score_gemma":0.00065686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02308505,"about_ca_topic_score_gemma":0.04595018,"domain_scores_codex":[0.9999485,0.000002606247,0.000003408913,0.00002413896,0.00001214706,0.000009118497],"domain_scores_gemma":[0.9999321,0.00001527822,0.0000161919,0.00000803092,0.00001223982,0.0000161906],"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":[0.0003026574,0.0000248218,0.006463271,0.0003038559,0.00003013715,0.0002576603,0.0004281035,0.0004334259,0.9777653,0.0002068094,0.0005932699,0.01319059],"study_design_scores_gemma":[0.00004601917,0.000630249,0.7729602,0.0001366083,0.000416204,0.001846124,0.001154739,0.002318195,0.1474391,0.0002948483,0.07268359,0.00007406715],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9564517,0.001099108,0.003401472,0.00009954508,0.00001800351,0.00004913868,0.03654375,0.0001913875,0.002145957],"genre_scores_gemma":[0.7864487,0.002317069,0.02073292,0.0001855305,0.00001823408,0.000119113,0.1788058,0.0001444358,0.01122834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02308505,"threshold_uncertainty_score":0.04590136,"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."}}