{"id":"W6924551175","doi":"10.15468/dl.pemxcr","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geodetic datum; Coordinate system; Matching (statistics); Download; Range (aeronautics); Geographic coordinate conversion","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":[0.0009829913,0.002062365,0.001624617,0.004583009,0.001095625,0.003099488,0.002951705,0.002118869,0.1562977],"category_scores_gemma":[0.006270345,0.0009110082,0.001451084,0.008776943,0.0004335743,0.002557611,0.002677827,0.002047923,0.2557398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001675308,"about_ca_system_score_gemma":0.002592539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02270623,"about_ca_topic_score_gemma":0.03482117,"domain_scores_codex":[0.9989029,0.000136487,0.000144905,0.0003928444,0.0002369334,0.0001858357],"domain_scores_gemma":[0.9975995,0.0006228215,0.0001916945,0.0006654615,0.0006747524,0.0002456627],"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":[0.00003643671,0.00001198145,0.0004673264,0.0005554067,0.00001670305,0.00001824545,0.00002583856,0.0001521069,0.0001350569,0.0004184208,0.9960356,0.002126766],"study_design_scores_gemma":[0.00005832547,0.000007748436,0.0015596,0.0001802644,0.00001301415,0.00003503671,0.00007134637,0.0002030661,0.0002050822,0.0008729253,0.9967762,0.00001753886],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004476029,0.0000323623,0.00006815621,0.00004447656,0.00001600968,0.000006602421,0.9983056,0.0007102416,0.0007717743],"genre_scores_gemma":[0.0001614384,0.00004153315,0.0002613216,0.0000519053,0.000003999386,0.00004173306,0.9986859,0.0002047195,0.000547485],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8437023,"threshold_uncertainty_score":0.5228678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01211720131075526,"score_gpt":0.1974929303221966,"score_spread":0.1853757290114413,"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."}}