{"id":"W3210335525","doi":"10.3389/fmars.2021.753531","title":"A Review of the Opportunities and Challenges for Using Remote Sensing for Management of Surface-Canopy Forming Kelps","year":2021,"lang":"en","type":"review","venue":"Frontiers in Marine Science","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada; Ministry of Forests; Fisheries and Oceans Canada; Tula Foundation; University of British Columbia; University of Victoria","funders":"Advanced Research Projects Agency; Advanced Research Projects Agency - Energy; Nature Conservancy; U.S. Department of Energy; National Science Foundation","keywords":"Kelp forest; Kelp; Threatened species; Environmental resource management; Remote sensing; Environmental science; Canopy; Ecosystem; Abundance (ecology); Ecology; Geography; Biology; Habitat","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001578137,0.000195146,0.001026607,0.0001340174,0.0001121953,0.00001614309,0.0004218025,0.00006626227,0.00001096751],"category_scores_gemma":[0.00009578015,0.0001307934,0.0001719742,0.0004036713,0.000387966,0.00009751636,0.0002747661,0.00008806194,4.521649e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001229702,"about_ca_system_score_gemma":0.0003001147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000287198,"about_ca_topic_score_gemma":0.0001757703,"domain_scores_codex":[0.998523,0.00008119535,0.0005303445,0.0003729338,0.0001845664,0.0003079791],"domain_scores_gemma":[0.9989865,0.0001534473,0.0004359075,0.0002839711,0.00009315571,0.0000470419],"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":[0.000003946041,0.000001898058,0.00007469751,0.08840016,0.00002338567,0.000002076872,0.00001053013,0.000002923507,9.980327e-8,0.00009928864,0.00005391449,0.9113271],"study_design_scores_gemma":[0.0001112669,0.00006071968,0.00003920849,0.06455309,0.0002705396,0.00004780324,0.0004406756,0.002803672,0.000002903746,0.0006407644,0.9308115,0.0002178514],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003312009,0.9950629,0.0008681831,0.00008196292,0.0005465835,0.001049788,0.0001121945,0.000003277471,0.002241966],"genre_scores_gemma":[0.000002175762,0.8737414,0.1258729,0.000039227,0.00001766259,6.557586e-7,0.0000513734,0.000003843084,0.000270682],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9307576,"threshold_uncertainty_score":0.5333601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1318532750545432,"score_gpt":0.2955909326427973,"score_spread":0.1637376575882541,"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."}}