{"id":"W7081584897","doi":"","title":"Functional Annotation of All Salmonid Genomes (FAASG): an international initiative supporting future salmonid research, conservation and aquaculture","year":2022,"lang":"en","type":"other","venue":"","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Directorate for Biological Sciences; Fiskeri - og havbruksnæringens forskningsfond; U.S. Department of Agriculture; Norges Forskningsråd; National Institute of Food and Agriculture; Genome British Columbia; Corporación de Fomento de la Producción","keywords":"Genome; Aquaculture; Leverage (statistics); Genomics; Genome project; Sustainability; Annotation; Fish <Actinopterygii>","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024189,0.001035961,0.0004182013,0.002591151,0.001082658,0.001727087,0.001230311,0.0008613917,0.01429569],"category_scores_gemma":[0.002524691,0.000225816,0.000650664,0.00325517,0.0005880775,0.001445082,0.002284712,0.0009768783,0.01084365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115068,"about_ca_system_score_gemma":0.003838569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01074262,"about_ca_topic_score_gemma":0.01298462,"domain_scores_codex":[0.9994784,0.00009364932,0.00002860223,0.0001416619,0.0001896409,0.0000680375],"domain_scores_gemma":[0.9986308,0.0002301485,0.0001422687,0.0001743175,0.0004598286,0.0003625429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000480304,0.0001324948,0.007095692,0.001694349,0.00008632084,0.0003772451,0.0005520347,0.002029677,0.07043304,0.03357279,0.3220442,0.5615019],"study_design_scores_gemma":[0.00004073206,0.00007190243,0.009757128,0.0003018177,0.0000363454,0.000248435,0.0001773679,0.003236048,0.01119873,0.01212895,0.9627595,0.00004314884],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.08000435,0.02042821,0.2618746,0.02365195,0.002988186,0.0007104555,0.3051378,0.04669028,0.2585142],"genre_scores_gemma":[0.07269453,0.01016434,0.3190367,0.003091668,0.0004433471,0.0005820345,0.5376843,0.00667834,0.04962473],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01429569,"threshold_uncertainty_score":0.04782385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06629679137361975,"score_gpt":0.3218729556197849,"score_spread":0.2555761642461651,"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."}}