{"id":"W3133931223","doi":"10.1594/pangaea.913907","title":"Metadata and NCBI-Accession numbers of 16S data for seawater, sediment, biofilm, and Vazella pourtalesii sponges from the Scotian Shelf (Canada) in summer 2016 and 2017","year":2020,"lang":"en","type":"dataset","venue":"Publishing Network for Geoscientific and Environmental Data (PANGAEA) (Alfred Wegener Institute for Polar and Marine Research)","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020","keywords":"Metadata; Sediment; Accession; Oceanography; Seawater; Accession number (library science); Fishery; Geography; World Wide Web; Biology; Geology; Business; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.002224755,0.0003240605,0.0003700378,0.0001063688,0.0007984947,0.001081413,0.001360529,0.0002634178,0.00001147923],"category_scores_gemma":[0.0003867888,0.0002663499,0.00003759502,0.0001256114,0.001000716,0.0003674467,0.00371659,0.0002749253,4.626563e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002369198,"about_ca_system_score_gemma":0.0001793237,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6097987,"about_ca_topic_score_gemma":0.7364321,"domain_scores_codex":[0.9970236,0.0001521779,0.0004812823,0.001486227,0.0003541489,0.0005026097],"domain_scores_gemma":[0.997617,0.0001971339,0.0002533908,0.001613512,0.00004468235,0.0002742739],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001877287,0.00005846813,0.001029178,0.0002780249,0.0001538716,9.305114e-7,0.00001840926,0.000002121508,0.002378716,0.00005899827,0.9928052,0.003028347],"study_design_scores_gemma":[0.0009376625,0.00007048836,0.002582297,0.00007547546,0.0001609158,0.000007653281,0.0002196009,0.0006205947,0.0003828687,0.00006633233,0.9945755,0.0003005911],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01281577,0.006028531,0.0003908836,0.001449797,0.0006106459,0.001194064,0.9774992,0.000004279444,0.000006810179],"genre_scores_gemma":[0.005282378,0.01474097,0.001172677,0.0001633892,0.0003579691,0.00006226607,0.9775634,0.0000331485,0.0006237612],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1266333,"threshold_uncertainty_score":0.9999789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09872129538845689,"score_gpt":0.3163097125163096,"score_spread":0.2175884171278527,"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."}}