{"id":"W6962212424","doi":"10.15468/dl.y7unb4","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; Alien; Range (aeronautics); State (computer science)","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":[0.0009116274,0.002029642,0.00147222,0.004959708,0.000956149,0.002403249,0.002536952,0.001901493,0.1590798],"category_scores_gemma":[0.005818073,0.0008783261,0.001174066,0.009774622,0.0004449571,0.002051317,0.00249196,0.001738948,0.2178963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001417823,"about_ca_system_score_gemma":0.002268854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02028297,"about_ca_topic_score_gemma":0.03222559,"domain_scores_codex":[0.998998,0.0001346865,0.0001274525,0.0003592193,0.0002082537,0.0001724114],"domain_scores_gemma":[0.9976617,0.0006635684,0.0002272057,0.0005948643,0.0005859457,0.0002666921],"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":[0.00003391153,0.00001225901,0.0004414274,0.0005481822,0.00001435739,0.00001517887,0.00002255417,0.0001303106,0.000132507,0.0003539645,0.9968002,0.001495091],"study_design_scores_gemma":[0.00008168865,0.00001143171,0.002092802,0.0001895892,0.00001571251,0.00003896643,0.00007213151,0.0001588872,0.0002096147,0.0007842839,0.9963258,0.00001915742],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005047529,0.00002734466,0.00003937439,0.00003321955,0.00001248629,0.000005247421,0.9988146,0.0003780589,0.000639207],"genre_scores_gemma":[0.0001727776,0.00003364894,0.0001870888,0.00004585001,0.000003775361,0.00004228512,0.9988965,0.000145552,0.0004725849],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8409202,"threshold_uncertainty_score":0.5321749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}