{"id":"W2904992418","doi":"10.1017/s1431927618015234","title":"Multi-Angle Plasma Focused Ion Beam (FIB) Curtaining Artifact Correction Using a Fourier-Based Linear Optimization Model","year":2018,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Seismic Imaging and Inversion Techniques","field":"Earth and Planetary Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"University of Connecticut","keywords":"Artifact (error); Focused ion beam; Computer science; Discretization; Materials science; Segmentation; Sample (material); Image processing; Computer vision; Artificial intelligence; Optics; Algorithm; Image (mathematics); Ion; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006378323,0.0007180314,0.0004931467,0.0002803601,0.0002445038,0.0005797399,0.0008825379,0.0009267282,0.001738645],"category_scores_gemma":[0.0009044158,0.0004602952,0.0005679227,0.0002689922,0.0004374918,0.0005799717,0.0004768349,0.0007200341,0.0004830509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007794931,"about_ca_system_score_gemma":0.001302206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008426895,"about_ca_topic_score_gemma":0.007439374,"domain_scores_codex":[0.9998092,0.00003872669,0.000007621957,0.00003910517,0.00008493235,0.00002031855],"domain_scores_gemma":[0.9996902,0.0001405281,0.00004828333,0.00002177932,0.00008505468,0.00001423446],"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":[0.00001191267,0.0000107068,0.0001357099,0.00002206378,0.000007860342,0.00001576743,0.00001550607,0.9858305,0.003138923,0.001246909,0.0002875837,0.009276559],"study_design_scores_gemma":[0.000001512776,0.000004512827,0.00002135704,0.000001071676,0.000001209647,0.00000321548,0.000001172997,0.9990311,0.0005774169,0.0001638085,0.0001918272,0.000001952226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004736589,0.00003808184,0.9940835,0.00006393621,0.000006109864,0.00001929958,0.00002731402,0.0002283839,0.0007969297],"genre_scores_gemma":[0.2820814,0.0002157939,0.7085468,0.0001634042,0.00002218211,0.0003497364,0.0002086586,0.0004964721,0.007915646],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008426895,"threshold_uncertainty_score":0.0167557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02740593730814422,"score_gpt":0.2647025207131217,"score_spread":0.2372965834049775,"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."}}