{"id":"W7106565923","doi":"10.15468/dl.af592v","title":"Occurrence Download","year":2025,"lang":"","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Herbarium; Polygon (computer graphics); Data collection","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":[0.0008736494,0.001860496,0.001594636,0.005268828,0.001173543,0.002753271,0.002800718,0.002128985,0.1549024],"category_scores_gemma":[0.006495482,0.0008760844,0.001289797,0.01016516,0.0004134463,0.002553579,0.002585465,0.001937561,0.214482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001876101,"about_ca_system_score_gemma":0.002736415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02813402,"about_ca_topic_score_gemma":0.04760496,"domain_scores_codex":[0.9988267,0.0001430816,0.0001511583,0.0004188732,0.0002618382,0.0001984656],"domain_scores_gemma":[0.9972791,0.0007294547,0.0002428636,0.0007018565,0.0007543322,0.0002924236],"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":[0.00003448061,0.00001182013,0.0005001167,0.0005713693,0.00001500206,0.00001759382,0.00002393476,0.0001237151,0.0001190552,0.0003886232,0.9963738,0.001820292],"study_design_scores_gemma":[0.0000640259,0.000008893326,0.002029711,0.0001981136,0.00001385437,0.00004188794,0.00008765745,0.0001777173,0.0001919309,0.0007237787,0.9964449,0.0000175848],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004948099,0.00002931646,0.0000478986,0.00003861312,0.0000136043,0.00000520971,0.9987356,0.0004392831,0.0006410724],"genre_scores_gemma":[0.0001715957,0.00003467366,0.0002180375,0.00004380674,0.000003834737,0.00003776669,0.9988343,0.0001389289,0.0005170534],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8450976,"threshold_uncertainty_score":0.5182002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434536157882973,"score_gpt":0.2311093459842124,"score_spread":0.2167639844053826,"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."}}