{"id":"W3128443778","doi":"10.3390/rs13040623","title":"A Review of Remote Sensing of Submerged Aquatic Vegetation for Non-Specialists","year":2021,"lang":"en","type":"review","venue":"Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aquatic ecosystem; Environmental science; Water column; Remote sensing; Aquatic plant; Vegetation (pathology); Water quality; Environmental resource management; Computer science; Ecology; Geography; Macrophyte","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001244015,0.0007615144,0.00364492,0.0001463407,0.0001341881,0.000034348,0.000291843,0.0005263182,0.00001989433],"category_scores_gemma":[0.001349356,0.0006434585,0.001412456,0.001474861,0.0002431625,0.0001093019,0.0002215041,0.0004858146,0.00004665818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005900441,"about_ca_system_score_gemma":0.0001788925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003949552,"about_ca_topic_score_gemma":0.0001730596,"domain_scores_codex":[0.9949414,0.0005785329,0.002115433,0.0009681497,0.0008123075,0.0005841728],"domain_scores_gemma":[0.995703,0.0004405426,0.002421399,0.001101936,0.0001792715,0.0001538227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002917276,0.000008739831,3.357345e-8,0.07864857,0.00009866799,0.00002217236,0.0001075399,0.00001824372,0.0006738776,0.000001083002,0.001415467,0.9190027],"study_design_scores_gemma":[0.000184664,0.00003942989,0.000002094848,0.3934924,0.001464754,0.000349561,0.00001660561,0.02141237,0.000359187,0.00009267336,0.5819551,0.0006311498],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004468967,0.9694222,0.02509029,0.00006345216,0.000710548,0.002127808,0.000009816674,0.00004257652,0.002488608],"genre_scores_gemma":[0.00001252618,0.7962644,0.2028984,0.0001296111,0.0002653952,1.119646e-8,0.0001668157,0.0001046197,0.0001582326],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9183716,"threshold_uncertainty_score":0.9996017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03352137803457829,"score_gpt":0.3059464240139148,"score_spread":0.2724250459793365,"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."}}