{"id":"W3036270649","doi":"10.1080/01431161.2020.1750732","title":"Geometrical constrained independent component analysis for hyperspectral unmixing","year":2020,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Endmember; Hyperspectral imaging; Independent component analysis; Pixel; Computer science; Imaging spectrometer; Blind signal separation; Pattern recognition (psychology); Remote sensing; Artificial intelligence; Principal component analysis; Data set; Set (abstract data type); Spectrometer; Geography","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":[0.0002706621,0.0001480162,0.0003306122,0.0006463657,0.00003620865,0.0001296877,0.0002249584,0.00007168829,0.000009590583],"category_scores_gemma":[0.0004720862,0.0001505755,0.0003564696,0.0005343577,0.00004320476,0.0001594976,0.00002325159,0.0002813216,0.000005505364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000302477,"about_ca_system_score_gemma":0.00004366394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007449152,"about_ca_topic_score_gemma":0.000002684927,"domain_scores_codex":[0.9984481,0.00003088465,0.0006079274,0.0001511905,0.0005754809,0.0001864629],"domain_scores_gemma":[0.9986235,0.0001921762,0.0002535012,0.00009270351,0.0006750801,0.000162963],"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":[0.0002392928,0.00002849186,0.0001895437,0.00003381994,0.004283452,0.0004108621,0.001050812,0.2221409,0.3623625,0.0001016614,0.0005320021,0.4086266],"study_design_scores_gemma":[0.0007666125,0.0000479481,0.001450446,0.00003820902,0.000253821,0.0003041482,0.0001952701,0.977883,0.01716386,0.0001308803,0.001608698,0.0001570586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1905472,0.00009246173,0.8055989,0.002556529,0.0007448975,0.00007253434,0.000007325515,0.00005901335,0.0003211569],"genre_scores_gemma":[0.7714037,0.00002729962,0.2277996,0.0001586541,0.0005730962,8.34675e-9,0.0000104177,0.00002204426,0.000005175688],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7557421,"threshold_uncertainty_score":0.6140292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0322106287213605,"score_gpt":0.2686846749666232,"score_spread":0.2364740462452627,"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."}}