{"id":"W3098465848","doi":"","title":"Widefield lensless endoscopy with a multicore fiber","year":2016,"lang":"en","type":"article","venue":"LillOA (Université de Lille (University Of Lille))","topic":"Random lasers and scattering media","field":"Physics and Astronomy","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Research Council; Université Lille 1 - Sciences et Technologies; Azrieli Foundation; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; Aix-Marseille Université","keywords":"Wavefront; Aperiodic graph; Optics; Computer science; Multi-core processor; Frame rate; Refresh rate; Physics; Computer vision","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008771329,0.0002310068,0.0003773462,0.0001597578,0.0003634265,0.00001108778,0.0004162557,0.00009774566,0.006252509],"category_scores_gemma":[0.000003938378,0.0002015908,0.0002069495,0.0002254641,0.0002676373,0.0003287847,0.0002250946,0.0001317761,0.0001767767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001083928,"about_ca_system_score_gemma":0.00006856728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001109523,"about_ca_topic_score_gemma":0.0001739603,"domain_scores_codex":[0.9987885,0.00005427052,0.0001072603,0.0003825608,0.0002348765,0.0004324695],"domain_scores_gemma":[0.9989059,0.0001691652,0.0001811383,0.0004119906,0.00008892797,0.0002429008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.009927141,0.00130583,0.5218104,0.0003169561,0.0032077,0.001201179,0.03681557,0.0003430005,0.1073915,0.02551166,0.05687569,0.2352935],"study_design_scores_gemma":[0.1090511,0.003235396,0.1472962,0.002382016,0.002261816,0.0001561687,0.09005071,0.001665205,0.0544861,0.002725836,0.5803825,0.006306949],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9448311,0.00003088935,0.007057591,0.001657051,0.00008301647,0.0001987224,0.00009459097,0.00006365292,0.04598334],"genre_scores_gemma":[0.9689456,0.00002511252,0.002838354,0.00004348724,0.00006255444,4.784602e-7,0.00001378234,0.00002340243,0.02804721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5235068,"threshold_uncertainty_score":0.9946559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004012361409844471,"score_gpt":0.1502622692678232,"score_spread":0.1462499078579788,"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."}}