{"id":"W1952087875","doi":"","title":"Canadian Airborne Hyperspectral Imager Development","year":2005,"lang":"en","type":"article","venue":"Defense Technical Information Center (DTIC)","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Remote sensing; Hyperspectral imaging; Spectrometer; Imaging spectrometer; Field of view; Optics; Spectral resolution; Nadir; VNIR; Spectral bands; Sampling (signal processing); Detector; Ranging; Image resolution; Computer science; Physics; Satellite; Geology; Telecommunications; Spectral line","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001187048,0.0001583046,0.0001294817,0.0003033346,0.00008810202,0.0001014266,0.0001522263,0.0001394308,0.000385335],"category_scores_gemma":[0.00004644261,0.0001582181,0.00005453613,0.0002912875,0.00003000264,0.0007716335,0.00002577793,0.0002503307,0.003942829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005454957,"about_ca_system_score_gemma":0.00006467832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009668143,"about_ca_topic_score_gemma":0.0008463164,"domain_scores_codex":[0.9988517,0.000007195492,0.0004392256,0.00008544055,0.0001983237,0.0004181084],"domain_scores_gemma":[0.9993473,0.00001606546,0.00002469101,0.0001887316,0.00006571827,0.0003574759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001164151,0.0007458279,0.007981455,0.0006538765,0.0004725831,0.00004777889,0.006717971,0.0508374,0.007410692,0.1122395,0.3460677,0.4667087],"study_design_scores_gemma":[0.0007085864,0.00002026385,0.009231602,0.00002951917,0.00001247719,0.00004793166,0.00008171354,0.01804561,0.0055113,0.0000648458,0.965725,0.0005211418],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2447503,0.0002510653,0.1228746,0.00769665,0.001450761,0.001262637,0.0001845543,0.005151929,0.6163775],"genre_scores_gemma":[0.9661701,0.00001692152,0.03128461,0.002130035,0.00007509258,0.00001366474,0.0001516963,0.00001905577,0.0001388026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7214199,"threshold_uncertainty_score":0.9968327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007545881046044129,"score_gpt":0.1994318934181497,"score_spread":0.1918860123721056,"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."}}