{"id":"W2966500929","doi":"10.1017/s1431927619001843","title":"Extending Monte Carlo Simulations of Electron Microscopy Images and Hyperspectral Images in a User-Friendly Framework","year":2019,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Object Research Systems (Canada); McGill University","funders":"","keywords":"Library science; Object (grammar); Computer science; Art history; Sociology; History; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004427095,0.000386817,0.0007963959,0.0005100741,0.000171445,0.0002072391,0.0002999303,0.000204365,0.0002329554],"category_scores_gemma":[0.00005809818,0.0003739223,0.0001454887,0.00065091,0.0002916147,0.0004090414,0.0001338917,0.0003752342,0.00001304153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001244936,"about_ca_system_score_gemma":0.00007081422,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009046283,"about_ca_topic_score_gemma":0.0002309738,"domain_scores_codex":[0.9975124,0.0001403462,0.000595736,0.0008180419,0.0001977775,0.000735718],"domain_scores_gemma":[0.9988577,0.000179457,0.0002570117,0.0004997544,0.00009455315,0.0001115634],"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":[0.000113455,0.00009925881,0.02402754,0.0000729915,0.00004257202,0.000004442672,0.0004098135,0.00005155255,0.9745472,0.0003803583,0.0001928944,0.00005788805],"study_design_scores_gemma":[0.0004654367,0.0002894056,0.003084585,0.0001390413,0.0001475802,0.00001375316,0.000269017,0.0001102083,0.9943101,0.0004714019,0.0003274581,0.0003719952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899699,0.007046254,0.001999226,0.0001886052,0.00006638511,0.0003824781,0.000110828,0.0000924932,0.0001438014],"genre_scores_gemma":[0.947924,0.001179856,0.05012686,0.00009452203,0.0000302701,0.00001520716,0.0000100541,0.00004090191,0.0005783947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04812763,"threshold_uncertainty_score":0.9998713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005198796915431237,"score_gpt":0.2914766510200335,"score_spread":0.2862778541046022,"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."}}