{"id":"W3040494869","doi":"10.1017/s1431927600029494","title":"“Casino V2.0 : An Advance Simulation Tool for Scanning Electron Microscope Users”","year":2001,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Scanning electron microscope; Materials science; Electron microscope; Nanotechnology; Computer science; Computer graphics (images); Optics; Physics; Composite material","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":[0.0006371978,0.0004106097,0.0005604209,0.0002665988,0.0006258039,0.0003962815,0.0003596542,0.0001807153,0.0002034357],"category_scores_gemma":[0.00005325955,0.0004067738,0.0001816815,0.0004961572,0.0001627832,0.0007684861,0.00006467386,0.0001855416,0.00002642187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001720526,"about_ca_system_score_gemma":0.00008075551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001412888,"about_ca_topic_score_gemma":0.0001976381,"domain_scores_codex":[0.9973261,0.0001126751,0.0005387341,0.0009356443,0.0001833775,0.0009034504],"domain_scores_gemma":[0.9987541,0.0001067024,0.0002526373,0.0005512164,0.0001856225,0.0001496568],"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":[0.0003399002,0.0001094179,0.002423209,0.00002992555,0.00003502913,0.000003549055,0.0002374697,0.0002802304,0.9942992,0.0001745811,0.0003232097,0.001744318],"study_design_scores_gemma":[0.0005739322,0.0004625249,0.0004317463,0.0000377697,0.0002048305,0.00001936804,0.00006490888,0.001621836,0.9722619,0.0004761688,0.02334444,0.0005005914],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.893894,0.001838316,0.1030735,0.0001561828,0.00009195188,0.000508566,0.00004255698,0.0002834417,0.0001114101],"genre_scores_gemma":[0.9345353,0.0004882632,0.06257322,0.0006315013,0.0001586703,0.00008781312,0.0001016813,0.00006852176,0.00135509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04064121,"threshold_uncertainty_score":0.9998384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01123818947140361,"score_gpt":0.3175759005296547,"score_spread":0.3063377110582511,"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."}}