{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006355603,0.001370217,0.0011199,0.002077526,0.0007018132,0.0008583071,0.001486713,0.0009730406,0.002475629],"category_scores_gemma":[0.001163433,0.0007413745,0.00119069,0.001581998,0.0005349246,0.001800501,0.001196545,0.001366821,0.002889036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003217947,"about_ca_system_score_gemma":0.0008993985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002227709,"about_ca_topic_score_gemma":0.003533918,"domain_scores_codex":[0.999038,0.00008688636,0.00005239146,0.0002892047,0.0004846807,0.00004882075],"domain_scores_gemma":[0.9993361,0.0001160422,0.00006520837,0.00008252431,0.0003696487,0.00003048482],"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":[0.0001359534,0.000111843,0.001435908,0.0002661518,0.0001661546,0.0001285635,0.0001398717,0.03355528,0.1338615,0.003431008,0.005443015,0.8213248],"study_design_scores_gemma":[0.00002652903,0.00006543071,0.001792033,0.00002017395,0.00004546018,0.0003716442,0.00004362418,0.9019516,0.07752948,0.003295759,0.01477189,0.00008636203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002701153,0.00009133085,0.9956747,0.00003527739,0.00003770521,0.00002591651,0.00005890429,0.000999268,0.0003757552],"genre_scores_gemma":[0.02479149,0.0001329388,0.971613,0.00006607159,0.00004145417,0.00007650534,0.0003454783,0.0002682448,0.002664651],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002475629,"threshold_uncertainty_score":0.008281767,"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."}}