{"id":"W3142102071","doi":"10.3390/rs13071253","title":"Hyperspectral Image Classification via Multi-Feature-Based Correlation Adaptive Representation","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Science and Technology Department of Henan Province","keywords":"Classifier (UML); Computer science; Pattern recognition (psychology); Artificial intelligence; Hyperspectral imaging; Correlation; Regularization (linguistics); Sparse approximation; Feature selection; Tikhonov regularization; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008606977,0.0006836466,0.0009181193,0.001103829,0.000385192,0.0007793,0.001031983,0.0008829621,0.001005333],"category_scores_gemma":[0.001978533,0.0002442258,0.0009210631,0.001779957,0.0005330134,0.001350442,0.0009152793,0.00123466,0.0006095579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004125324,"about_ca_system_score_gemma":0.0008367845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002342167,"about_ca_topic_score_gemma":0.002249784,"domain_scores_codex":[0.9991654,0.0001409065,0.00003466581,0.0001966236,0.0003809727,0.00008137942],"domain_scores_gemma":[0.9993272,0.0001866693,0.0001126927,0.00009581214,0.0002485111,0.00002917252],"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":[0.0002043406,0.0002373546,0.002405428,0.0001734413,0.0001491503,0.0001774834,0.000148261,0.1543058,0.0711893,0.01403944,0.00721304,0.7497569],"study_design_scores_gemma":[0.000005983764,0.00004340842,0.0005405716,0.000007064476,0.00001943829,0.00008643488,0.00001404337,0.9898504,0.006378301,0.001598998,0.001439887,0.00001548379],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01914866,0.0004314035,0.9784226,0.0002060372,0.00004289017,0.00003785182,0.00005374894,0.0004622602,0.001194556],"genre_scores_gemma":[0.4785801,0.001155127,0.5141426,0.0004057565,0.0002049721,0.000194174,0.0007566496,0.000141732,0.004418795],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002342167,"threshold_uncertainty_score":0.00465709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03548999507354676,"score_gpt":0.2663929774890574,"score_spread":0.2309029824155106,"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."}}