{"id":"W4391033652","doi":"10.3389/fenvs.2023.1353447","title":"Editorial: Hyperspectral imaging in environmental monitoring and analysis","year":2024,"lang":"en","type":"editorial","venue":"Frontiers in Environmental Science","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Agriculture and Agri-Food Canada","funders":"","keywords":"Hyperspectral imaging; Remote sensing; Environmental science; Environmental monitoring; Geology; Environmental engineering","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":[0.004673408,0.003689127,0.003731621,0.003656826,0.003107409,0.008181206,0.003581609,0.01476569,0.02076555],"category_scores_gemma":[0.01843936,0.001105545,0.002632634,0.001784827,0.002578257,0.005678374,0.001709239,0.01877889,0.02457562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002521412,"about_ca_system_score_gemma":0.0021482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001375341,"about_ca_topic_score_gemma":0.003626331,"domain_scores_codex":[0.9959605,0.0006110034,0.0003760967,0.0005202121,0.002305874,0.0002261482],"domain_scores_gemma":[0.9839244,0.005944964,0.0007912114,0.0004341544,0.006575682,0.002329552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001807835,0.000009305229,0.0000124169,0.0001092143,0.000008173395,0.00006744602,0.00000465184,0.00002231476,0.00004112897,0.0001862333,0.9955223,0.003998709],"study_design_scores_gemma":[0.00002798364,0.00001611518,0.0001685582,0.0002997502,0.00001964935,0.0002651479,0.00001772633,0.0001474273,0.00008807983,0.0008888035,0.9980459,0.00001470587],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00002363594,0.006119307,0.0001732247,0.0237393,0.9674587,0.00001835816,0.00004303803,0.00006235954,0.002362039],"genre_scores_gemma":[0.0002652115,0.004487809,0.0001080191,0.01454038,0.9706113,0.00001805787,0.00003314337,0.00004172691,0.009894348],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02076555,"threshold_uncertainty_score":0.06946766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002972172972085964,"score_gpt":0.2017696045931117,"score_spread":0.1987974316210257,"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."}}