{"id":"W2980365667","doi":"10.1016/j.dib.2019.104631","title":"Concentration dataset for 4 essential and 5 non-essential elements in fish collected in Arctic and sub-Arctic territories of the Nenets Autonomous and Arkhangelsk regions of Russia","year":2019,"lang":"en","type":"article","venue":"Data in Brief","topic":"Indigenous Studies and Ecology","field":"Health Professions","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Government Council on Grants, Russian Federation; Center for Outcomes Research and Evaluation, Yale School of Medicine","keywords":"Arctic; The arctic; Indigenous; Fish <Actinopterygii>; Russian federation; Geography; Fishery; Environmental protection; Physical geography; Ecology; Oceanography; Biology; Regional science; Geology","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":[0.0007700227,0.0005619301,0.0008842705,0.002885941,0.0005162646,0.0005885715,0.0007744451,0.0004940568,0.005631571],"category_scores_gemma":[0.001839256,0.0002690304,0.0006959952,0.003318916,0.0002432519,0.0002950902,0.00109829,0.0004224606,0.002715714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007249232,"about_ca_system_score_gemma":0.001520207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04211836,"about_ca_topic_score_gemma":0.04884086,"domain_scores_codex":[0.9991934,0.0001127601,0.0001667271,0.0002411301,0.000200886,0.00008506285],"domain_scores_gemma":[0.9987401,0.0001836451,0.0003479712,0.000145503,0.00051621,0.00006645293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001172776,0.0002817461,0.7970278,0.007657236,0.001431416,0.0008783988,0.001762486,0.001513952,0.01181028,0.001380368,0.1005842,0.07449935],"study_design_scores_gemma":[0.0000473385,0.0001373301,0.9050542,0.0004013278,0.0002825297,0.0004493532,0.0009238205,0.0003947323,0.001809614,0.0002933902,0.09016235,0.00004401099],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1306103,0.001840763,0.002054372,0.000169525,0.00007772895,0.0001446163,0.8599644,0.0002419014,0.004896367],"genre_scores_gemma":[0.2278684,0.001724347,0.00724996,0.0001764679,0.00007347792,0.0008336778,0.7580083,0.00009645271,0.003968875],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04211836,"threshold_uncertainty_score":0.08374643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0245800334012624,"score_gpt":0.3355735141996281,"score_spread":0.3109934807983657,"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."}}