{"id":"W2086301489","doi":"10.2138/am.2007.2252","title":"Manganese valence imaging in Mn minerals at the nanoscale using STEM-EELS","year":2006,"lang":"en","type":"article","venue":"American Mineralogist","topic":"Geological and Geochemical Analysis","field":"Earth and Planetary Sciences","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Valence (chemistry); Chemistry; Analytical Chemistry (journal); Manganese; Spectroscopy; Electron energy loss spectroscopy; Pyrolusite; Valence electron; Transmission electron microscopy; Materials science; Electron; Nanotechnology; Physics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001696844,0.0001822185,0.0002708749,0.00006082467,0.0001611722,0.00004645271,0.0003035205,0.00002447884,0.001743702],"category_scores_gemma":[0.00002897111,0.0001066906,0.0001143346,0.0006778406,0.0008560357,0.00009116466,0.00004394919,0.0001224175,0.0001584678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001279984,"about_ca_system_score_gemma":0.00001112383,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1271517,"about_ca_topic_score_gemma":0.06311352,"domain_scores_codex":[0.9985092,0.0001204645,0.0003005616,0.0003736482,0.0002265358,0.0004696235],"domain_scores_gemma":[0.9993216,0.0001969133,0.000134197,0.0002420018,0.00002784485,0.00007743415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001389367,0.00002151147,0.9753051,0.000003366879,0.000004005982,0.00007371781,0.000017655,0.006291239,0.009744934,0.0000125288,0.001673809,0.006838246],"study_design_scores_gemma":[0.0001959936,0.00004599137,0.9787712,0.00001229562,0.00003089187,0.00007336764,0.0001958611,0.01273079,0.001063359,0.001501367,0.005026343,0.000352534],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903999,0.0009082954,0.00002276881,0.002280477,0.00005094002,0.00008321736,0.00007412804,0.00002731716,0.006152933],"genre_scores_gemma":[0.9948668,0.00002443007,0.0004956182,0.0008401873,0.0001066359,0.000001998676,0.000140165,0.000002962307,0.003521129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06403815,"threshold_uncertainty_score":0.9991688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219572589982735,"score_gpt":0.2133795535090122,"score_spread":0.2011838276091848,"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."}}