{"id":"W7090362168","doi":"10.15468/dl.cth2nd","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":"Geodetic datum; Coordinate system; Matching (statistics); Download; Range (aeronautics); Geographic coordinate conversion","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":[],"consensus_categories":[],"category_scores_codex":[0.0009417681,0.001859446,0.001440539,0.004874807,0.001039303,0.002755735,0.002769061,0.00185489,0.1544598],"category_scores_gemma":[0.006358679,0.0008736065,0.001302033,0.008913123,0.0004188688,0.002447723,0.002565699,0.001939941,0.2370258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001616261,"about_ca_system_score_gemma":0.002529221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02197072,"about_ca_topic_score_gemma":0.03508264,"domain_scores_codex":[0.9988905,0.0001409193,0.000152038,0.0003859847,0.0002451566,0.0001854283],"domain_scores_gemma":[0.9975836,0.0006200114,0.0001972939,0.0006780088,0.0006704472,0.0002506055],"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":[0.00002859153,0.000009752413,0.0003989732,0.0004471847,0.00001301583,0.00001600727,0.00002420573,0.0001210287,0.0001134766,0.0004006198,0.9965694,0.001857783],"study_design_scores_gemma":[0.00005369243,0.000006447864,0.001542131,0.0001513313,0.00001108204,0.00003527205,0.00007260097,0.0001745253,0.0001837144,0.0007476687,0.9970068,0.00001471665],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005035108,0.000031841,0.00007325927,0.00004688589,0.00001702146,0.000007094727,0.9981646,0.0007173328,0.0008916116],"genre_scores_gemma":[0.0001747577,0.00003664996,0.0002690016,0.00005072185,0.000004098117,0.00004368487,0.9986684,0.0002030239,0.000549636],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1544598,"threshold_uncertainty_score":0.5167196,"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."}}