{"id":"W1996972086","doi":"10.1007/s10661-007-9855-3","title":"Remote sensing of aquatic vegetation: theory and applications","year":2007,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":319,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Vegetation (pathology); Wetland; Environmental science; Aquatic plant; Remote sensing; Macrophyte; Aquatic ecosystem; Biomass (ecology); Ecosystem; Ecology; Geography; Biology","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":[0.0004548797,0.0005355625,0.0005642811,0.000858074,0.0002644848,0.001013868,0.0007853957,0.001188082,0.001186071],"category_scores_gemma":[0.0009425643,0.000320051,0.0003839545,0.001492771,0.001522821,0.001120392,0.0006423162,0.000894487,0.0003412087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004667204,"about_ca_system_score_gemma":0.0003448588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001596735,"about_ca_topic_score_gemma":0.001260821,"domain_scores_codex":[0.9997529,0.00005650095,0.00001014634,0.00005728551,0.0001027432,0.00002045552],"domain_scores_gemma":[0.9995613,0.0003028176,0.00003127587,0.00003780542,0.00005356656,0.00001325929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006206799,0.0001233567,0.003322739,0.0009089945,0.00009332387,0.0002542648,0.0003305813,0.1818705,0.02676979,0.2829094,0.004542735,0.4988122],"study_design_scores_gemma":[0.00002692724,0.0001317306,0.004153235,0.0001756389,0.00006815155,0.0006892482,0.0002078696,0.6318011,0.007065673,0.3165606,0.03904557,0.00007415496],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02299199,0.04838279,0.9129945,0.001602319,0.0003063371,0.0000594798,0.0001616969,0.000232652,0.01326821],"genre_scores_gemma":[0.6034188,0.06787387,0.3167832,0.0008054465,0.001676624,0.0002046475,0.0003191929,0.00007471,0.008843494],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001596735,"threshold_uncertainty_score":0.003967822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006357212995918932,"score_gpt":0.2516717122015762,"score_spread":0.2453144992056573,"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."}}