{"id":"W7107970792","doi":"10.15468/dl.aubkhg","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); Range (aeronautics); Polygon (computer graphics); Data set","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":[0.0008952722,0.001803135,0.001680611,0.005384596,0.001090292,0.00278869,0.002730814,0.002026706,0.1983034],"category_scores_gemma":[0.006685191,0.0009408134,0.001173847,0.01007407,0.0003971139,0.002560318,0.002684678,0.001905439,0.2519014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001779121,"about_ca_system_score_gemma":0.002552563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02404184,"about_ca_topic_score_gemma":0.03735482,"domain_scores_codex":[0.9988839,0.0001291919,0.0001487972,0.0003949064,0.0002504657,0.0001927398],"domain_scores_gemma":[0.9974958,0.0006873838,0.0002412907,0.0006148503,0.0006861679,0.0002744983],"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":[0.00003120405,0.000009628438,0.0004385361,0.0006557707,0.00001442622,0.00001624268,0.00002480928,0.0001105159,0.0001110641,0.000411778,0.9962907,0.001885402],"study_design_scores_gemma":[0.0000576546,0.000006980224,0.001680549,0.0002153104,0.00001353726,0.00003710765,0.00007593334,0.000135687,0.0001657618,0.000656676,0.9969389,0.00001582971],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003700686,0.00002961043,0.0000477721,0.00003516694,0.00001114174,0.000004638927,0.9987015,0.0004323768,0.0007007862],"genre_scores_gemma":[0.0001724962,0.00004254638,0.0002333639,0.00005092824,0.000003756311,0.00004048375,0.998678,0.0001840095,0.0005943271],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8016965,"threshold_uncertainty_score":0.6633911,"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."}}