{"id":"W6943776263","doi":"10.15468/dl.vj72hv","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Set (abstract data type); Identification (biology); Download","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":[0.0009128798,0.002104347,0.001316431,0.004278873,0.001009499,0.002252172,0.002867381,0.001880403,0.1063038],"category_scores_gemma":[0.005515454,0.0008241628,0.001220799,0.008133863,0.0004505627,0.002118917,0.002383659,0.001945234,0.1721096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001598171,"about_ca_system_score_gemma":0.002439542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0237534,"about_ca_topic_score_gemma":0.04265751,"domain_scores_codex":[0.9989404,0.0001393187,0.0001411453,0.000364604,0.0002485616,0.0001659796],"domain_scores_gemma":[0.9977513,0.0005496984,0.0002048444,0.0006298985,0.0005966598,0.0002676967],"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":[0.00002935862,0.00001366175,0.0003774902,0.0003671611,0.00001197937,0.00001415991,0.00002063459,0.0001228977,0.0001108429,0.0003704462,0.9971091,0.001452259],"study_design_scores_gemma":[0.0000814441,0.00001068369,0.001928726,0.0001454266,0.00001286262,0.00004651165,0.0000748655,0.0002426251,0.0002360289,0.000866028,0.9963366,0.00001822948],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007436965,0.00003281175,0.00006531492,0.00004833395,0.00001612269,0.000007797846,0.9982559,0.0006598121,0.0008395065],"genre_scores_gemma":[0.0001729425,0.00002945182,0.0002544513,0.0000449591,0.000003475556,0.00003847191,0.9988531,0.0001399143,0.0004632375],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8936962,"threshold_uncertainty_score":0.3556217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03761864349018661,"score_gpt":0.2888078212483628,"score_spread":0.2511891777581762,"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."}}