{"id":"W1998982972","doi":"10.2113/gscanmin.41.4.905","title":"CHARACTERIZATION OF ARSENATE-FOR-SULFATE SUBSTITUTION IN SYNTHETIC JAROSITE USING X-RAY DIFFRACTION AND X-RAY ABSORPTION SPECTROSCOPY","year":2003,"lang":"en","type":"article","venue":"The Canadian Mineralogist","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Jarosite; Arsenate; Characterization (materials science); Sulfate; Absorption (acoustics); Substitution (logic); X-ray crystallography; X-ray absorption spectroscopy; X-ray; Crystallography; Materials science; Powder diffraction; Chemistry; Diffraction; Absorption spectroscopy; Analytical Chemistry (journal); Nuclear chemistry; Mineralogy; Arsenic; Metallurgy; Nanotechnology; Optics; Environmental chemistry; Physics; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003336763,0.00008670228,0.00009090286,0.00008070825,0.0001691597,0.00002507367,0.00005100769,0.00005800485,0.0001028171],"category_scores_gemma":[0.00007031875,0.00007585272,0.00002096532,0.0001741318,0.0001886007,0.0001824537,0.000006326993,0.0000646141,0.000008982805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004813402,"about_ca_system_score_gemma":0.00004260892,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03878361,"about_ca_topic_score_gemma":0.2493412,"domain_scores_codex":[0.999321,0.00007368361,0.0001838428,0.0001638939,0.00008355748,0.0001739976],"domain_scores_gemma":[0.9996672,0.0000235167,0.0001076079,0.0001172514,0.00001380289,0.00007059835],"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":[0.000008876211,0.00001124206,0.007202394,0.000005605086,0.000002197299,7.050738e-7,0.0002993696,0.001613904,0.9868034,0.00337599,0.000007837707,0.0006685454],"study_design_scores_gemma":[0.0006231627,0.00004536933,0.9444358,0.00003811491,0.00003113331,0.00001199851,0.0001160193,0.02939554,0.01966416,0.0006570579,0.004754178,0.000227428],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954642,0.000009542491,0.002782439,0.0003257431,0.0001104247,0.0003398811,0.00001630122,0.000006827079,0.0009446527],"genre_scores_gemma":[0.9990959,0.0000194298,0.0004253961,0.0001014184,0.00001406277,0.00001357514,0.00004597848,0.000007468862,0.0002768264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9671392,"threshold_uncertainty_score":0.9676172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506859351311512,"score_gpt":0.2250837428717371,"score_spread":0.2100151493586219,"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."}}