{"id":"W1213406169","doi":"10.1117/12.2189114","title":"Performance characterization of a pressure-tuned wide-angle Michelson interferometric spectral filter for high spectral resolution lidar","year":2015,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"LightMachinery (Canada)","funders":"Langley Research Center","keywords":"Optics; Interferometry; Michelson interferometer; Astronomical interferometer; Wavefront sensor; Spectral resolution; Wavefront; Optical path length; Tilt (camera); Absorption (acoustics); Filter (signal processing); Optical filter; Materials science; Interference (communication); Wavelength; Physics; Spectral line; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000596137,0.0003868566,0.0003303048,0.00055044,0.0005049579,0.0006274963,0.0007762205,0.0007667263,0.001321467],"category_scores_gemma":[0.0009951048,0.0001637547,0.0003006416,0.0004428736,0.0002667634,0.0006085197,0.000256724,0.0003764033,0.0005068279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009435285,"about_ca_system_score_gemma":0.0004189151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001752087,"about_ca_topic_score_gemma":0.002165216,"domain_scores_codex":[0.9993541,0.00003606423,0.00002375086,0.0001129043,0.0003792644,0.00009396507],"domain_scores_gemma":[0.999134,0.0002160223,0.0001809196,0.00008143012,0.0002916981,0.00009598062],"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":[0.0001783005,0.0001163656,0.002097985,0.00004715948,0.00001483778,0.00008314531,0.0000856437,0.0005980277,0.9912133,0.0002165572,0.0002891746,0.005059469],"study_design_scores_gemma":[0.00001142973,0.0009653873,0.01096442,0.000004735717,0.00001545064,0.0001214465,0.0000403593,0.007078866,0.9789153,0.0000268527,0.001834875,0.00002093737],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9931877,0.0002571429,0.004611585,0.00008657201,0.00002578673,0.00003554671,0.0002989449,0.0001948617,0.001301899],"genre_scores_gemma":[0.9938323,0.0001305182,0.004512052,0.00004681489,0.00001306928,0.00002745319,0.0002618509,0.00003115901,0.00114464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001752087,"threshold_uncertainty_score":0.006845772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01342957830046793,"score_gpt":0.2228038002828878,"score_spread":0.2093742219824199,"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."}}