{"id":"W6943385469","doi":"10.15468/dl.vzmx9q","title":"Occurrence Download","year":2023,"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); Range (aeronautics); Real world data","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":[0.0008603124,0.001917077,0.001484099,0.004923193,0.001002005,0.002628143,0.002662901,0.002047978,0.173269],"category_scores_gemma":[0.005804447,0.0009175522,0.001207503,0.01039496,0.0004233559,0.002452729,0.002613657,0.002052602,0.2400483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001772651,"about_ca_system_score_gemma":0.002443985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02685988,"about_ca_topic_score_gemma":0.0417848,"domain_scores_codex":[0.9989774,0.0001327556,0.0001320087,0.0003522213,0.000232042,0.0001734064],"domain_scores_gemma":[0.997693,0.0006343342,0.0002014365,0.0005814878,0.0006357766,0.0002538845],"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":[0.00002610176,0.0000100854,0.0003408706,0.0004754172,0.00001180392,0.00001481922,0.00002430162,0.0001131104,0.00009170856,0.0003744504,0.9969902,0.00152716],"study_design_scores_gemma":[0.00005769719,0.000006489442,0.001495108,0.000182146,0.00001112462,0.00003624007,0.00007633298,0.0001523298,0.0001630935,0.0007386152,0.9970647,0.0000162261],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004164427,0.00002725982,0.0000544877,0.00004145245,0.00001278175,0.000005555642,0.9985153,0.0004917137,0.0008097172],"genre_scores_gemma":[0.0001751468,0.00003848504,0.0002540328,0.00005108855,0.000003673899,0.00004378212,0.9986261,0.0002031545,0.0006045255],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.826731,"threshold_uncertainty_score":0.5796427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}