{"id":"W6961859358","doi":"10.15468/dl.jzf7ma","title":"Occurrence Download","year":2024,"lang":"en","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); Polygon (computer graphics); Range (aeronautics); R package","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":[0.0008904677,0.002338706,0.001956761,0.00523749,0.001276239,0.003813016,0.003244726,0.002269282,0.234205],"category_scores_gemma":[0.006692749,0.001037183,0.001693116,0.009280566,0.0003942724,0.003822212,0.003568674,0.002289841,0.3637849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001661274,"about_ca_system_score_gemma":0.002385694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01768041,"about_ca_topic_score_gemma":0.02956252,"domain_scores_codex":[0.9987184,0.0001436112,0.0001600851,0.0004819605,0.0002827863,0.0002131326],"domain_scores_gemma":[0.9975016,0.0005773444,0.0001935613,0.0007349992,0.0007129192,0.0002796585],"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":[0.00004005777,0.00001211643,0.0003634732,0.0005181817,0.00001382702,0.00001916043,0.00002321003,0.0000895983,0.0001053305,0.0003667166,0.9957604,0.00268798],"study_design_scores_gemma":[0.00004623643,0.000009518405,0.001073326,0.0001495281,0.00001120274,0.00003907056,0.00006893816,0.00017909,0.0001678745,0.0007484839,0.9974906,0.00001607015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006404144,0.00005935944,0.0001093308,0.00007416351,0.00002995317,0.000009443473,0.9964985,0.00173705,0.001418225],"genre_scores_gemma":[0.000224884,0.00006599628,0.0004067927,0.00009275396,0.000008117204,0.00005141139,0.9974993,0.0005180635,0.001132711],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.765795,"threshold_uncertainty_score":0.7834937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708767307206114,"score_gpt":0.2335971948231368,"score_spread":0.2165095217510757,"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."}}