{"id":"W2793879578","doi":"10.3390/photonics5010003","title":"High Throughput AOTF Hyperspectral Imager for Randomly Polarized Light","year":2018,"lang":"en","type":"article","venue":"Photonics","topic":"Optical and Acousto-Optic Technologies","field":"Physics and Astronomy","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hyperspectral imaging; Optics; Throughput; Liquid crystal tunable filter; Materials science; Optical filter; Filter (signal processing); Spectral resolution; Spectral imaging; Optoelectronics; Wavelength; Physics; Computer science; Spectral line; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.000102625,0.0001820309,0.0002823136,0.00003357618,0.0001830465,0.00007172763,0.0002538548,0.00007458407,0.000576685],"category_scores_gemma":[0.00002337414,0.0001425968,0.0001759246,0.00009830364,0.0001705811,0.000117948,0.00008289082,0.0001606332,0.000182105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002215071,"about_ca_system_score_gemma":0.00004497146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000643903,"about_ca_topic_score_gemma":0.00000148146,"domain_scores_codex":[0.9989694,0.000009134666,0.0001963416,0.0002929697,0.0001090856,0.000423009],"domain_scores_gemma":[0.9993672,0.00008028822,0.00006555134,0.0003214546,0.0001083075,0.00005716217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005247692,0.0004810383,0.0005426216,0.00002595365,0.0003008396,0.000003305775,0.0004539104,0.000004428072,0.4894833,0.4932555,0.008503517,0.006420801],"study_design_scores_gemma":[0.00652629,0.0004134953,0.000100105,0.00001934158,0.0001416424,0.000002124833,0.0005486979,0.002120965,0.7697575,0.1541363,0.06569117,0.000542376],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.914427,0.0001741207,0.05480099,0.006621191,0.001029001,0.00108049,0.000197869,0.000503312,0.02116605],"genre_scores_gemma":[0.9140946,0.000004501844,0.08360285,0.0001522776,0.0004521803,0.00008186689,0.00001784591,0.00002766123,0.00156617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3391192,"threshold_uncertainty_score":0.6314297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007882474929506231,"score_gpt":0.2439391189245955,"score_spread":0.2360566439950893,"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."}}