{"id":"W3075086259","doi":"10.1117/1.oe.59.8.083104","title":"Lensless inline digital holography versus Fourier ptychography: phase estimation of a large transparent bead","year":2020,"lang":"en","type":"article","venue":"Optical Engineering","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université de Strasbourg","keywords":"Optics; Ptychography; Digital holography; Holography; Phase retrieval; Phase (matter); Digital holographic microscopy; Microscopy; Materials science; Phase imaging; Fourier transform; Biological specimen; Computer science; Diffraction; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003121834,0.0001459969,0.0001976668,0.00006316143,0.00001939211,0.0000222686,0.0001106458,0.00002759375,0.0000168535],"category_scores_gemma":[0.00002173794,0.0001511847,0.0001285423,0.0002453523,0.00003525055,0.0002071941,0.00002760089,0.0001656872,0.00000254728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005455857,"about_ca_system_score_gemma":0.000006337173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000100799,"about_ca_topic_score_gemma":2.567599e-8,"domain_scores_codex":[0.9992745,0.00000269515,0.0002046129,0.0001788679,0.0001233081,0.000215999],"domain_scores_gemma":[0.9996365,0.00005090383,0.00003677216,0.0001329195,0.00002908184,0.0001138455],"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":[0.0008216702,0.002297184,0.00498198,0.0003872946,0.0008337597,0.00003266808,0.001148074,0.4376962,0.0251777,0.210218,0.0001650981,0.3162403],"study_design_scores_gemma":[0.00393983,0.0004487628,0.0003385158,0.00008134932,0.00009601482,5.368106e-7,0.00007104936,0.9617286,0.03034464,0.0006999293,0.001784465,0.0004663347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1568403,0.00002750895,0.8422886,0.0001537643,0.00005094569,0.0001045122,0.0001035927,0.0001552996,0.0002754493],"genre_scores_gemma":[0.9182988,9.422475e-7,0.08149484,0.00001061879,0.00007668595,0.00001713007,0.00007821838,0.00002222819,5.833599e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7614585,"threshold_uncertainty_score":0.6165132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02046112743386645,"score_gpt":0.3004782487819901,"score_spread":0.2800171213481236,"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."}}