{"id":"W3175715531","doi":"10.5194/isprs-annals-v-3-2021-15-2021","title":"USE OF LANDSAT-8 OLI IMAGERY AND LOCAL INDIGENOUS KNOWLEDGE FOR EELGRASS MAPPING IN EEYOU ISTCHEE","year":2021,"lang":"en","type":"article","venue":"ISPRS annals of the photogrammetry, remote sensing and spatial information sciences","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Niskamoon Corporation; University of Victoria; University of New Brunswick","funders":"Mitacs; Niskamoon Corporation","keywords":"Bay; Ecosystem services; Zostera marina; Habitat; Environmental science; Geography; Shore; Ecosystem; Ecosystem health; Fishery; Remote sensing; Environmental resource management; Oceanography; Ecology; Seagrass; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0005258035,0.0001553583,0.0001397828,0.001824168,0.0003837307,0.0007035697,0.0002060542,0.0001687765,0.0006181641],"category_scores_gemma":[0.0009770868,0.0001296406,0.0001458232,0.00121171,0.0002498287,0.0004015505,0.0004261341,0.0001643211,0.000135335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001425276,"about_ca_system_score_gemma":0.00102593,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4720688,"about_ca_topic_score_gemma":0.8121732,"domain_scores_codex":[0.999827,0.00003184011,0.00001058345,0.00004926239,0.00003474487,0.00004660303],"domain_scores_gemma":[0.9994314,0.0001006104,0.00009111553,0.00003527772,0.0002750595,0.00006646989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001555108,0.0001092939,0.9282224,0.0001290421,0.00007259988,0.0004090653,0.003188199,0.001772005,0.01404218,0.0001097014,0.0005872448,0.05120268],"study_design_scores_gemma":[0.00000392125,0.00002131708,0.992191,0.00003577577,0.00001798723,0.00004787998,0.00323757,0.002871891,0.0008723223,0.00001230913,0.0006796679,0.000008448892],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982538,0.00005322115,0.000289752,0.0000175845,8.964575e-7,0.00002127895,0.000688998,0.000009593479,0.0006648994],"genre_scores_gemma":[0.9966797,0.00006508057,0.001561546,0.00001051152,7.77337e-7,0.00001565722,0.001117729,0.00000328494,0.0005457609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5279312,"threshold_uncertainty_score":0.938642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06786521052748581,"score_gpt":0.276934092240086,"score_spread":0.2090688817126002,"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."}}