{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003077557,0.0003731437,0.000365359,0.000405743,0.0001404145,0.0005890791,0.0003427498,0.0004231433,0.0004491878],"category_scores_gemma":[0.0007256652,0.0002606197,0.0001763963,0.0004888058,0.000234407,0.0002365439,0.000233163,0.0001968794,0.0001553295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001992012,"about_ca_system_score_gemma":0.000217659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006878115,"about_ca_topic_score_gemma":0.001098023,"domain_scores_codex":[0.9996108,0.00005949568,0.00005703888,0.00005136964,0.0001840455,0.00003730075],"domain_scores_gemma":[0.9996992,0.00004007349,0.00009200678,0.00002934794,0.0000979621,0.00004139702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004723061,0.000008551807,0.0005454177,0.0000351889,0.00000607014,0.00004405959,0.00001960957,0.0001475223,0.998321,0.00003273116,0.00001148208,0.000781141],"study_design_scores_gemma":[0.000009956087,0.0002776374,0.007434579,0.00001041226,0.00002285372,0.0001621617,0.00008259773,0.001649563,0.9872936,0.00003798182,0.003004826,0.00001387664],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973012,0.0002202588,0.001603981,0.00001918475,0.000007120095,0.00001745867,0.0003144238,0.00003637347,0.0004800975],"genre_scores_gemma":[0.991837,0.0003832489,0.005923418,0.0000239592,0.000004771944,0.00004612935,0.0008565646,0.00004075738,0.0008842122],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006878115,"threshold_uncertainty_score":0.001627564,"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."}}