{"id":"W7116413334","doi":"10.15468/dl.avmjw9","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); Data archive; Polygon (computer graphics)","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":[0.0007481509,0.002586059,0.002063588,0.0063919,0.001580827,0.004074801,0.003006003,0.002827399,0.2614134],"category_scores_gemma":[0.006330121,0.0009883059,0.001709749,0.01026442,0.0004464122,0.004411007,0.003541909,0.002562363,0.3762836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001798591,"about_ca_system_score_gemma":0.002599011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02071906,"about_ca_topic_score_gemma":0.04467235,"domain_scores_codex":[0.998688,0.0001527745,0.0001828255,0.0004567127,0.0003119208,0.0002076975],"domain_scores_gemma":[0.9975632,0.000613047,0.0001892784,0.0005764239,0.000746674,0.0003112413],"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":[0.00004364564,0.00001437759,0.0003514806,0.0006550702,0.00001281983,0.00003008209,0.00002423336,0.00009737642,0.0001145999,0.0004503765,0.9950823,0.003123774],"study_design_scores_gemma":[0.00005118127,0.00001127687,0.001005973,0.0001873721,0.00001224597,0.00006623878,0.00008600194,0.0002383627,0.0001569294,0.001071416,0.9970942,0.0000187571],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000976363,0.0001474458,0.0001656114,0.0001059013,0.00004322733,0.00001447784,0.9944474,0.001927281,0.003050998],"genre_scores_gemma":[0.0003113355,0.0001110981,0.0005126487,0.0001171255,0.00001155397,0.00004671259,0.9969329,0.0004027538,0.001553905],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7385865,"threshold_uncertainty_score":0.8745151,"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."}}