{"id":"W1209462256","doi":"10.1117/12.2188276","title":"Integrated computational imaging system for enhanced polarimetric measurements","year":2015,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Polarimetry; Computer science; Rotation (mathematics); Noise (video); Detector; Probabilistic logic; Process (computing); Optics; Physics; Computer vision; Artificial intelligence; Telecommunications","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":[0.0007820554,0.0003386372,0.0004319575,0.0002566113,0.00007576948,0.0001502815,0.0006783635,0.0001675998,0.00000399636],"category_scores_gemma":[0.0008162429,0.0003018068,0.0004603393,0.0007707825,0.0001206727,0.0005432798,0.00007553068,0.0002684653,0.000004610905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004619424,"about_ca_system_score_gemma":0.00005453546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008572436,"about_ca_topic_score_gemma":8.185166e-8,"domain_scores_codex":[0.9976463,1.988608e-8,0.0007742274,0.0003179933,0.0008281163,0.0004333165],"domain_scores_gemma":[0.9963239,0.0001447956,0.0002112305,0.00005212597,0.00304159,0.0002263457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001514431,0.0001680201,0.000989698,0.001637626,0.0009271136,7.36887e-8,0.0002676685,0.01574606,0.6595397,0.3110277,0.008589108,0.0009557664],"study_design_scores_gemma":[0.003564803,0.0002781193,0.0007370061,0.0005542865,0.0003011721,0.00001775132,0.00279241,0.6922171,0.2927849,0.001710613,0.004246773,0.0007951534],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984598,0.0002239012,0.008850604,0.0003878064,0.000715085,0.0007075561,0.000103146,0.000330957,0.004082929],"genre_scores_gemma":[0.8167123,0.000009069658,0.1825957,0.00005635037,0.000304758,0.0001137001,0.00003968403,0.00008950856,0.00007898375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.676471,"threshold_uncertainty_score":0.9999434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02123131545561405,"score_gpt":0.2351380997692224,"score_spread":0.2139067843136084,"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."}}