{"id":"W3047378372","doi":"10.1016/j.ultramic.2020.113092","title":"Analysis of nanoscale fluid inclusions in geomaterials by atom probe tomography: Experiments and numerical simulations","year":2020,"lang":"en","type":"article","venue":"Ultramicroscopy","topic":"Advanced Materials Characterization Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; College of Engineering, University of Wisconsin-Madison; Mitacs","keywords":"Atom probe; Channelling; Materials science; Transmission electron microscopy; Nanoscopic scale; Electron backscatter diffraction; Electron tomography; Brittleness; Scanning transmission electron microscopy; Nanostructure; Mineralogy; Nanotechnology; Chemical physics; Chemistry; Composite material; Microstructure","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002189041,0.0002776712,0.0002607096,0.0002742428,0.0003707848,0.0003987008,0.000430919,0.0007536687,0.001006965],"category_scores_gemma":[0.0008003425,0.0002174946,0.0001908543,0.0002818384,0.000832476,0.0008227222,0.0003295656,0.0002851578,0.0001366764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005042115,"about_ca_system_score_gemma":0.0005779124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003246732,"about_ca_topic_score_gemma":0.002102049,"domain_scores_codex":[0.9999189,0.0000105018,0.000002895906,0.00001843006,0.00003559436,0.00001362832],"domain_scores_gemma":[0.9996817,0.0001743537,0.00004498035,0.00003571626,0.00004991588,0.00001339773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002567578,0.0002097316,0.005030927,0.0001554678,0.00001489893,0.0002584135,0.0002359943,0.7838249,0.1895499,0.01090875,0.0003833832,0.009170847],"study_design_scores_gemma":[0.000006985687,0.00002154507,0.0007359979,0.000003133455,0.000002329736,0.00002013783,0.0000230908,0.980688,0.01781097,0.0004936193,0.0001885703,0.000005606299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358367,0.0001975756,0.05987141,0.0001739239,0.00001311134,0.0000446697,0.0002177,0.0001567935,0.003488081],"genre_scores_gemma":[0.9877464,0.00008786353,0.01149039,0.000009115955,0.000002794455,0.00001938635,0.00005305864,0.000017809,0.000573138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003246732,"threshold_uncertainty_score":0.00645566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008339990776502118,"score_gpt":0.2603725922157346,"score_spread":0.2520326014392325,"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."}}