{"id":"W4285818913","doi":"10.3133/fs20223053","title":"North Dakota and Landsat","year":2022,"lang":"en","type":"article","venue":"Fact sheet","topic":"Rangeland and Wildlife Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Waterfowl; Geological survey; Wetland; Archaeology; Habitat; Geology; Ecology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003652923,0.0008439248,0.0003627291,0.001291385,0.001699395,0.001887274,0.0005624622,0.0004473148,0.3607684],"category_scores_gemma":[0.0005757586,0.0005037426,0.0002943835,0.002360519,0.0002201435,0.0009959808,0.0008438432,0.0008125702,0.2403013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00161807,"about_ca_system_score_gemma":0.003187105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1958852,"about_ca_topic_score_gemma":0.4048741,"domain_scores_codex":[0.9997367,0.00001520034,0.00001568961,0.00008826582,0.00009045667,0.00005360669],"domain_scores_gemma":[0.9994459,0.00002058539,0.00003299392,0.00006622977,0.0003584187,0.00007595699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00003261028,0.00001383163,0.001626986,0.00007166032,0.000008353523,0.00002918014,0.0000603597,0.00003464269,0.0003265349,0.0006331801,0.9791015,0.01806111],"study_design_scores_gemma":[0.00001531504,0.000004204047,0.009433883,0.00005612789,0.000005029782,0.00002477207,0.0001451758,0.0001115932,0.0002089481,0.0001481271,0.9898366,0.00001020332],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005342784,0.001070863,0.00165312,0.002157298,0.001302493,0.000309979,0.4881662,0.00423371,0.4957636],"genre_scores_gemma":[0.01198263,0.001164405,0.00428971,0.000839313,0.0001229229,0.0003894039,0.3026837,0.002109179,0.6764187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3607684,"threshold_uncertainty_score":0.9117863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005756705742415564,"score_gpt":0.1768122072928356,"score_spread":0.17105550155042,"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."}}