{"id":"W4300889849","doi":"10.1080/07038992.2021.1992594","title":"A New Endmember Extraction Method Based on Least Squares","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Space Agency; Concordia University","funders":"","keywords":"Endmember; Hyperspectral imaging; Data cube; Pixel; Pattern recognition (psychology); Cube (algebra); Artificial intelligence; Computer science; Spectral signature; Curse of dimensionality; Least-squares function approximation; Noise (video); Mathematics; Algorithm; Geography; Image (mathematics); Remote sensing; Data mining; Statistics; Combinatorics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002870652,0.0001614648,0.000225693,0.0003845677,0.00009316435,0.0001486365,0.00006808338,0.0001128146,0.00006789988],"category_scores_gemma":[0.0003943156,0.0001799605,0.0001314177,0.0003332103,0.00001938126,0.0001590462,0.000002264943,0.0004492879,0.00002536523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005180227,"about_ca_system_score_gemma":0.001174247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001383127,"about_ca_topic_score_gemma":0.01054895,"domain_scores_codex":[0.9988859,0.000108064,0.0003507499,0.0001442941,0.0002134529,0.0002975606],"domain_scores_gemma":[0.9985972,0.000131003,0.0001243574,0.0002685297,0.0002974094,0.0005814908],"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":[0.000007389399,0.000001366195,0.000007009938,0.00001811329,0.0000251927,0.001084484,0.0001566324,0.06054931,0.03619715,0.000006806825,0.004542739,0.8974038],"study_design_scores_gemma":[0.0003714959,0.00002864288,0.0008824264,0.0004128492,0.00005130585,0.002438296,0.0001568901,0.8485516,0.06127982,0.0001683282,0.08543187,0.0002264942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0141987,0.0002517358,0.974045,0.001318868,0.001512586,0.00004667505,0.00000206308,0.00004073785,0.008583584],"genre_scores_gemma":[0.3964176,0.000006747405,0.6025912,0.0001759244,0.0004642012,2.166454e-9,0.000003834275,0.00005298985,0.000287463],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8971773,"threshold_uncertainty_score":0.7338578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.021790979310712,"score_gpt":0.2614371411031999,"score_spread":0.2396461617924879,"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."}}