{"id":"W6944478876","doi":"10.18739/a2rf5kh5j","title":"Mercury content in floodplain sediments from the Yukon River Basin, Alaska, 2022","year":2024,"lang":"en","type":"dataset","venue":"UC Santa Barbara","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Permafrost; Floodplain; Mercury (programming language); Hydrology (agriculture); STREAMS; Water quality","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004526564,0.0009729045,0.0005433956,0.003193683,0.000863482,0.001178294,0.000910809,0.0008612461,0.006330535],"category_scores_gemma":[0.001473234,0.0004860133,0.0005135163,0.007117866,0.0003003929,0.0005869189,0.001198619,0.0004058383,0.006968216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001456125,"about_ca_system_score_gemma":0.002414322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2454658,"about_ca_topic_score_gemma":0.3928852,"domain_scores_codex":[0.9996169,0.00002759313,0.0000662708,0.0001362693,0.00009011306,0.0000628976],"domain_scores_gemma":[0.9990119,0.0001029352,0.0001319249,0.0001596939,0.000515923,0.00007762131],"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":[0.0004008554,0.0001105061,0.1222253,0.002933814,0.0004101116,0.0004254757,0.0007129573,0.003250755,0.002529606,0.0005900779,0.8441115,0.0222991],"study_design_scores_gemma":[0.00019522,0.00003250514,0.3919912,0.0005430254,0.0001530825,0.0001661647,0.001179775,0.001326722,0.001833568,0.0005500608,0.6019496,0.00007913592],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004648572,0.00008567782,0.00002752451,0.00003166396,0.000008672097,0.000005295577,0.9944966,0.0001396265,0.000556412],"genre_scores_gemma":[0.005033015,0.00009479152,0.000226142,0.0000152382,0.00000304193,0.00003540361,0.9939527,0.00002066787,0.0006189129],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2454658,"threshold_uncertainty_score":0.4880739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02602095662049192,"score_gpt":0.2636508872983974,"score_spread":0.2376299306779055,"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."}}