{"id":"W6945151275","doi":"10.21966/gv88-hv41","title":"Spatial extent of eelgrass (Zostera marina) meadows from monitoring sites within Gwaii Haanas (2016, 2017, 2018) mapped using remote piloted aerial systems","year":2016,"lang":"en","type":"dataset","venue":"Hakai Institute","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shapefile; Georeference; Citizen science; Transect; Drone; Aerial survey; Aerial photography; Geocoding; Workflow; Data collection","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001710748,0.0002775725,0.0002061131,0.002800992,0.0004598331,0.0004422958,0.0003299026,0.0001262359,0.003655412],"category_scores_gemma":[0.0003570864,0.0002083703,0.0001858392,0.003456543,0.0001903184,0.0002453339,0.0005457131,0.0002266115,0.00095024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000999257,"about_ca_system_score_gemma":0.001367856,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.439321,"about_ca_topic_score_gemma":0.7665569,"domain_scores_codex":[0.999836,0.000007900227,0.00001085926,0.00004858926,0.00006964951,0.000027104],"domain_scores_gemma":[0.9995894,0.00002601761,0.00008270179,0.00003656887,0.0002042202,0.00006115257],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005138909,0.0000960923,0.7613215,0.0009884149,0.0002630528,0.0007338379,0.006847493,0.003022956,0.03166715,0.0005448934,0.06816539,0.1258352],"study_design_scores_gemma":[0.00001356884,0.00001539455,0.9649891,0.00007048889,0.00003344315,0.00009752229,0.001812957,0.0009026097,0.001176656,0.00003301735,0.03083504,0.00002014451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.761222,0.0003726448,0.001788055,0.00008255927,0.0000297943,0.0002401419,0.2198026,0.000805648,0.01565655],"genre_scores_gemma":[0.7084789,0.0005661285,0.01554848,0.00004705805,0.00001546283,0.0006564106,0.2640597,0.0002814737,0.0103464],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.560679,"threshold_uncertainty_score":0.8735278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07221470957633339,"score_gpt":0.2966995680933742,"score_spread":0.2244848585170408,"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."}}