{"id":"W2950075164","doi":"10.1039/c9ja00083f","title":"Using multiple micro-analytical techniques for evaluating quantitative synchrotron-XRF elemental mapping of hydrothermal pyrite","year":2019,"lang":"en","type":"article","venue":"Journal of Analytical Atomic Spectrometry","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Science Foundation","keywords":"Pyrite; Hydrothermal circulation; Synchrotron; Materials science; Analytical Chemistry (journal); Mineralogy; Chemistry; Geology; Environmental chemistry; Physics; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001333017,0.0002258121,0.0007141524,0.0006593115,0.00004798323,0.00004295614,0.0002213204,0.0001212555,0.0003548492],"category_scores_gemma":[0.0002935494,0.0001943893,0.0005158724,0.00042931,0.00006344343,0.000271642,0.00003596181,0.0004996126,0.00001241055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003651524,"about_ca_system_score_gemma":0.00006606242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008755866,"about_ca_topic_score_gemma":8.727997e-7,"domain_scores_codex":[0.9978219,0.00006819767,0.001116898,0.0001860063,0.0004429457,0.0003640569],"domain_scores_gemma":[0.9987046,0.0004481144,0.0003933153,0.0001543329,0.0001647741,0.0001348253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001880693,0.0001131574,0.006589886,0.0002166526,0.0007297707,0.000007399958,0.00008018014,0.001803691,0.9851119,0.002044544,0.00007115011,0.003043616],"study_design_scores_gemma":[0.0009880491,0.0005943858,0.0009370957,0.0002451046,0.0002158448,0.0001286725,0.0005984402,0.8927866,0.1027503,0.0002308783,0.0002794013,0.0002452118],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8996406,0.0002472287,0.09883154,0.00003665248,0.0002027538,0.0002554533,0.00001387346,0.00003474978,0.0007371346],"genre_scores_gemma":[0.8814295,0.00001604525,0.11827,0.00002814482,0.0001711601,0.00000122516,0.000002449025,0.00003635632,0.00004513936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8909829,"threshold_uncertainty_score":0.7926968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05434806594664116,"score_gpt":0.3497813512835373,"score_spread":0.2954332853368961,"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."}}