{"id":"W2045209031","doi":"10.1364/oe.11.002268","title":"Using coherence to measure two-time correlation functions","year":2003,"lang":"en","type":"article","venue":"Optics Express","topic":"Material Dynamics and Properties","field":"Materials Science","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Coherence (philosophical gambling strategy); Speckle pattern; Measure (data warehouse); Optics; Coherence theory; Spectroscopy; Intensity (physics); Statistical physics; Correlation; Physics; Materials science; Coherence length; Mathematics; Quantum mechanics; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002635128,0.0001030357,0.0001162188,0.00003449033,0.0001771671,0.000173759,0.0001220289,0.00004647876,0.001103014],"category_scores_gemma":[0.00009504184,0.00009225307,0.00002156849,0.00008115829,0.00003156138,0.0001382693,0.00004105919,0.00004455879,0.0006761262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003155193,"about_ca_system_score_gemma":0.0000402467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006632363,"about_ca_topic_score_gemma":0.000005334894,"domain_scores_codex":[0.9991847,0.00008004844,0.000161071,0.0001982649,0.0001794227,0.0001964862],"domain_scores_gemma":[0.9994891,0.000023113,0.00005130611,0.0002336199,0.0001202445,0.00008263627],"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":[0.00001715195,0.00001563931,0.0000584375,0.000005734244,0.000002110848,9.82464e-7,0.0001459601,0.02470347,0.9725391,0.002320234,0.0001184097,0.00007275392],"study_design_scores_gemma":[0.000852212,0.0002047401,0.0001443326,0.0002182413,0.0000766784,0.00003875094,0.0002163495,0.1265917,0.8555902,0.001864076,0.01327419,0.0009285686],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8914706,0.00003423548,0.08787692,0.00002766999,0.001358994,0.0002373462,0.0000413815,0.00006779429,0.01888504],"genre_scores_gemma":[0.9671707,9.818011e-7,0.02956843,0.00005834072,0.00006596882,0.00001595344,0.00000537401,0.00001725005,0.003096956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.116949,"threshold_uncertainty_score":0.9998101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0410844159394176,"score_gpt":0.252797287499635,"score_spread":0.2117128715602175,"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."}}