{"id":"W1979621288","doi":"10.1016/j.aca.2010.03.027","title":"Determination of Mn, Fe, Co, Ni, Cu, Zn, Cd and Pb in seawater using high resolution magnetic sector inductively coupled mass spectrometry (HR-ICP-MS)","year":2010,"lang":"en","type":"article","venue":"Analytica Chimica Acta","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":312,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research Council Canada; National High Magnetic Field Laboratory; National Science Foundation","keywords":"Chemistry; Seawater; Inductively coupled plasma mass spectrometry; Isotope dilution; Certified reference materials; Chelating resin; Inductively coupled plasma; Analytical Chemistry (journal); Geotraces; Mass spectrometry; Ammonium acetate; Standard addition; Standard solution; Matrix (chemical analysis); Detection limit; Chromatography; Metal; High-performance liquid chromatography; Metal ions in aqueous solution","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000277079,0.0001640709,0.0002520077,0.0001846044,0.00009944638,0.00003164467,0.0001298495,0.0001062432,0.001235793],"category_scores_gemma":[0.0001217672,0.0001485911,0.00003816906,0.0003991124,0.0003243901,0.0003088477,0.00009158723,0.0002282105,0.00002309621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001085376,"about_ca_system_score_gemma":0.00001764399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005543997,"about_ca_topic_score_gemma":0.0006267713,"domain_scores_codex":[0.998763,0.00005359832,0.0003025075,0.0003016827,0.0002931513,0.0002860609],"domain_scores_gemma":[0.9994575,0.00007249427,0.0001440359,0.0002071725,0.00002311654,0.00009564099],"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":[0.00002439314,0.00004846129,0.05676526,0.00001245173,0.00001080493,0.000001928584,0.0003312472,0.000001440513,0.9424448,0.00002593303,0.0001792594,0.0001540204],"study_design_scores_gemma":[0.0006557538,0.0001418088,0.9211972,0.00002570085,0.00007888707,0.0000164253,0.000162566,0.01549686,0.06093257,0.0008745482,0.0001465917,0.0002710967],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977868,0.00000561748,0.00009670117,0.0003112855,0.00008556963,0.0001876975,0.00001558727,0.0000147515,0.001495947],"genre_scores_gemma":[0.9949882,0.00003780284,0.004607832,0.00006540654,0.00004520611,0.000004139014,0.00001257569,0.00001378988,0.0002250258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8815122,"threshold_uncertainty_score":0.9996772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804506957910217,"score_gpt":0.2605399627598381,"score_spread":0.2424948931807359,"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."}}