{"id":"W6962941097","doi":"10.15468/dl.w6sdmn","title":"Occurrence Download","year":2024,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Polygon (computer graphics); Matching (statistics); Range (aeronautics)","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":[0.0009211782,0.002182674,0.001857361,0.006285927,0.001430806,0.003945718,0.003241266,0.002203662,0.2021465],"category_scores_gemma":[0.007109571,0.0009832624,0.001723821,0.01027925,0.000412346,0.004173701,0.003631381,0.002263364,0.306661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001698787,"about_ca_system_score_gemma":0.002624356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01739615,"about_ca_topic_score_gemma":0.03201032,"domain_scores_codex":[0.9985685,0.0001550571,0.000201016,0.00051891,0.0003327685,0.0002236878],"domain_scores_gemma":[0.9972302,0.0006762429,0.0002234504,0.0007932506,0.0007929798,0.0002838133],"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":[0.00004456841,0.00001417732,0.0005076757,0.0006473949,0.00001562225,0.00002774993,0.0000306363,0.0001060872,0.0001325826,0.0005109548,0.9943616,0.003600928],"study_design_scores_gemma":[0.000038286,0.000009284062,0.001212772,0.0001595398,0.00001157992,0.00005355453,0.00008491489,0.0001999551,0.0001808047,0.0008507356,0.9971814,0.00001730892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009310264,0.00008510854,0.0001665142,0.00009101237,0.0000385873,0.00001222237,0.9956501,0.00198192,0.00188137],"genre_scores_gemma":[0.0002885323,0.00008365342,0.0005616244,0.00009614713,0.00001028159,0.00005563243,0.9971831,0.0004765122,0.001244532],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7978535,"threshold_uncertainty_score":0.6762473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708767307206114,"score_gpt":0.2335971948231368,"score_spread":0.2165095217510757,"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."}}