{"id":"W2384405226","doi":"","title":"Anomaly Detection Algorithm Based on NSCT Decomposition in Hyperspectral Imagery","year":2014,"lang":"en","type":"article","venue":"Infrared Technology","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Hyperspectral imaging; Residual; Anomaly detection; Artificial intelligence; Transformation (genetics); Computer science; Anomaly (physics); Pattern recognition (psychology); Remote sensing; Decomposition; Computer vision; Algorithm; Geology; Physics","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":[],"consensus_categories":[],"category_scores_codex":[0.0001491721,0.0001078242,0.0001388604,0.0005321966,0.00007741222,0.00002578083,0.0001083626,0.0001929568,0.00007599821],"category_scores_gemma":[0.00005776478,0.00009466145,0.00003562633,0.0004161892,0.00006696906,0.00006729319,0.000003724755,0.0002412499,0.0001280212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001160712,"about_ca_system_score_gemma":0.00001600049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004019274,"about_ca_topic_score_gemma":0.000762499,"domain_scores_codex":[0.999207,0.00005955607,0.0001471398,0.0002377038,0.000097025,0.0002516083],"domain_scores_gemma":[0.9995986,0.00008476283,0.00004441556,0.0002156501,0.00001865816,0.00003791273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004176295,0.00002322697,0.03129437,0.000002970674,0.000003153808,0.00003250889,0.00001113738,0.001640682,0.00108142,0.00002779796,0.00005635351,0.9657846],"study_design_scores_gemma":[0.0007865487,0.0006979028,0.2579603,0.00003256341,0.000006952775,0.00006671487,0.00005922675,0.7183549,0.01166404,0.007228761,0.002893443,0.0002486625],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717301,0.00003981174,0.00821995,0.0006575076,0.0002464237,0.00009521366,0.000008422774,0.0002907803,0.0187118],"genre_scores_gemma":[0.9877586,0.000005339165,0.01186298,0.0002451174,0.00005844916,3.841502e-7,0.00003068875,0.000003755076,0.00003465019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9655359,"threshold_uncertainty_score":0.3860182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004632572085888286,"score_gpt":0.2027271830200096,"score_spread":0.1980946109341213,"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."}}