{"id":"W4386023890","doi":"10.36967/2300010","title":"Land cover map of Yukon-Charley Rivers National Preserve, 2022","year":2023,"lang":"en","type":"report","venue":"National Park Service","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Cover (algebra); Land cover; Geography; Hydrology (agriculture); Physical geography; Archaeology; Forestry; Fishery; Environmental science; Geology; Land use; Ecology; Biology; Engineering; Geotechnical engineering","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":[0.0002207301,0.0006308651,0.0002734483,0.002241627,0.0007240188,0.0006638697,0.0006786052,0.0003440345,0.02127445],"category_scores_gemma":[0.0006174666,0.0003315864,0.0002786126,0.005371294,0.0001230388,0.0004326006,0.0004966479,0.0003228998,0.009795372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002225785,"about_ca_system_score_gemma":0.009807386,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7396708,"about_ca_topic_score_gemma":0.8377203,"domain_scores_codex":[0.9997658,0.00001473963,0.00002191026,0.00003568032,0.00009556075,0.00006629212],"domain_scores_gemma":[0.9991993,0.00002029903,0.00004142235,0.00004602187,0.0006244733,0.00006835136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002540784,0.0001228847,0.07334128,0.0005402255,0.00008743445,0.0002477608,0.0003292389,0.001005275,0.0009678936,0.0005345778,0.8920488,0.03052063],"study_design_scores_gemma":[0.00007557328,0.00003106562,0.6636416,0.0001114964,0.00003736178,0.00009129258,0.0008216865,0.0009670779,0.0006264271,0.0001118119,0.3334636,0.000021022],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0236442,0.0002292712,0.0002178745,0.0002632363,0.0001115479,0.0001906002,0.9465671,0.0001801753,0.02859601],"genre_scores_gemma":[0.04712633,0.0004071041,0.0009264647,0.000143585,0.00001637702,0.0003095515,0.8918062,0.00007751515,0.05918685],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7396708,"threshold_uncertainty_score":0.5237246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1407764175158086,"score_gpt":0.3267152248938097,"score_spread":0.1859388073780011,"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."}}