{"id":"W4296736820","doi":"10.1364/cosi.2022.cth4c.3","title":"Wide angle imaging system image simulation for accurate neural network performances prediction.","year":2022,"lang":"en","type":"article","venue":"Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; ImmerVision (Canada)","funders":"","keywords":"Artificial neural network; Computer science; Pipeline (software); Distortion (music); Artificial intelligence; Image (mathematics); Computer vision","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":[0.0009168764,0.00037484,0.0003880764,0.0001767225,0.001246216,0.0008691645,0.0008314116,0.0000417143,0.00002978217],"category_scores_gemma":[0.00004503562,0.0003799075,0.00009906619,0.0004148197,0.0001731899,0.0009947,0.0007018782,0.0004415024,0.000005733192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001649287,"about_ca_system_score_gemma":0.0000607931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009218898,"about_ca_topic_score_gemma":0.000001689909,"domain_scores_codex":[0.9972276,0.00009178595,0.0006043852,0.0007735445,0.0005843747,0.0007182838],"domain_scores_gemma":[0.9983999,0.0003709786,0.0003050736,0.0005331211,0.0002370989,0.0001538111],"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":[0.001283963,0.0007198948,0.02990376,0.001455872,0.0004381033,0.0001117495,0.003764372,0.4443007,0.02236803,0.1085068,0.04174205,0.3454047],"study_design_scores_gemma":[0.0009356114,0.0001216184,0.0002644046,0.00007293421,0.00006098712,0.00001984143,0.0005109771,0.9923532,0.001307624,0.0005412035,0.003383141,0.0004284542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06395947,0.002091279,0.9089396,0.001369413,0.004863059,0.002991673,0.0001714511,0.002400027,0.013214],"genre_scores_gemma":[0.9739006,0.00003197015,0.02454057,0.0004284318,0.0003083724,0.0006079883,0.00004547717,0.00004203464,0.00009462347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9099411,"threshold_uncertainty_score":0.9998653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01928303849423643,"score_gpt":0.2570243766452535,"score_spread":0.2377413381510171,"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."}}