{"id":"W7107950395","doi":"10.15468/dl.ud5r5a","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); Robustness (evolution); 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":[0.0008938497,0.001778599,0.001550933,0.005762164,0.001014373,0.002804978,0.002604924,0.001840896,0.1729859],"category_scores_gemma":[0.006316244,0.0009103692,0.001162915,0.01059591,0.0004041292,0.002425476,0.002620328,0.00190316,0.2443196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001632477,"about_ca_system_score_gemma":0.00253229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02207262,"about_ca_topic_score_gemma":0.03754026,"domain_scores_codex":[0.9989165,0.0001237461,0.0001498968,0.0003825476,0.0002454793,0.000181906],"domain_scores_gemma":[0.9973601,0.0006771203,0.000259339,0.0006586085,0.000747448,0.0002973647],"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":[0.00002889666,0.000009721101,0.0004350435,0.0005900343,0.00001395517,0.00001549111,0.0000236382,0.00009828177,0.0001098445,0.0004043184,0.9964839,0.001786927],"study_design_scores_gemma":[0.0000521616,0.000006395786,0.001684412,0.000190074,0.00001214391,0.00003265553,0.00006937931,0.0001143177,0.0001630984,0.0006541947,0.9970064,0.00001486838],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003803689,0.00002697513,0.00004446755,0.00003368764,0.00001206045,0.000004655777,0.998728,0.0003937351,0.0007184205],"genre_scores_gemma":[0.0001656698,0.00004037996,0.000228487,0.00004830982,0.000004242012,0.0000387229,0.9986954,0.0001721731,0.0006067057],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8270141,"threshold_uncertainty_score":0.5786955,"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."}}