{"id":"W1969184429","doi":"10.1109/tgrs.2011.2160646","title":"A Bicriteria-Optimization-Approach-Based Dimensionality-Reduction Model for the Color Display of Hyperspectral Images","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Hyperspectral imaging; Computer science; Dimensionality reduction; Artificial intelligence; Visualization; Curse of dimensionality; Pattern recognition (psychology); Mathematical optimization; Mathematics","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":[0.000221313,0.0001473622,0.0001407052,0.0001321869,0.0003630962,0.00003820923,0.00007563687,0.00006887148,0.000001526742],"category_scores_gemma":[0.00001393623,0.0001140385,0.00007619319,0.0002707212,0.0003479056,0.0001800976,8.228551e-7,0.000118834,5.224904e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004465712,"about_ca_system_score_gemma":0.00004255482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007086076,"about_ca_topic_score_gemma":0.000005601257,"domain_scores_codex":[0.9991321,0.00002433412,0.0002267112,0.0002556615,0.0001591038,0.0002020777],"domain_scores_gemma":[0.9994145,0.00008286146,0.00005461477,0.0002465406,0.0001499493,0.00005153723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003688406,0.00002868498,4.423614e-8,0.00003291907,0.00001304748,3.016537e-7,0.0005461111,0.8388852,0.120322,0.0000119805,0.000009248153,0.0401136],"study_design_scores_gemma":[0.0001845762,0.00003362746,0.00002897414,0.00003640343,0.00005432269,0.00002507738,0.0002410797,0.8974569,0.1017639,0.00005432341,0.000003191524,0.0001176003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0300099,0.00003010212,0.9688625,0.0001603103,0.0004100716,0.0003083535,0.00001899824,0.00009943305,0.0001002693],"genre_scores_gemma":[0.5242888,0.00003140227,0.475573,0.00002025423,0.00001365327,3.840366e-7,0.000001611114,0.00001503155,0.00005586271],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4942789,"threshold_uncertainty_score":0.4650355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03629205643565588,"score_gpt":0.2370224482504469,"score_spread":0.200730391814791,"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."}}