{"id":"W2579656072","doi":"10.3390/rs9010088","title":"The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data","year":2017,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":196,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Rio Tinto; Česká geologická služba","keywords":"Hyperspectral imaging; Drone; Remote sensing; Computer science; Terrain; Photogrammetry; Toolbox; Computer vision; Artificial intelligence; Geology; Geography; Cartography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005275287,0.001064394,0.0004197133,0.001159594,0.000309106,0.0009337825,0.0009284928,0.00045197,0.01277645],"category_scores_gemma":[0.00195017,0.0004667344,0.0006715018,0.0006677598,0.0003502517,0.001187703,0.001243074,0.00122687,0.0112602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002207366,"about_ca_system_score_gemma":0.0005999248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002073813,"about_ca_topic_score_gemma":0.003069167,"domain_scores_codex":[0.999696,0.00003356868,0.0000207072,0.00007302013,0.0001460133,0.00003071248],"domain_scores_gemma":[0.9994247,0.0001266988,0.00005518978,0.0001751711,0.0001792169,0.0000391493],"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":[0.00037181,0.0001217685,0.003021563,0.0007606387,0.0001704906,0.0006455517,0.0005410651,0.04334143,0.1285524,0.01209903,0.0656326,0.7447416],"study_design_scores_gemma":[0.0001336033,0.0001221004,0.008808194,0.000222138,0.0000511759,0.001304941,0.0002964627,0.4768536,0.2088177,0.01435535,0.2888445,0.0001902192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009021385,0.0001958013,0.9491687,0.0001033145,0.00006771832,0.00008681209,0.002955526,0.03569727,0.002703489],"genre_scores_gemma":[0.07476119,0.0006319355,0.8926576,0.0001503127,0.00005538747,0.0003349476,0.0146511,0.008808579,0.007948998],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01277645,"threshold_uncertainty_score":0.04274154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1046317570439365,"score_gpt":0.3335407806333736,"score_spread":0.2289090235894371,"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."}}