{"id":"W6961907598","doi":"10.15468/dl.nnpp44","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); Data set; State (computer science)","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":[0.0008689372,0.001988911,0.001619547,0.005165768,0.001149758,0.002739936,0.002913192,0.002273495,0.1571755],"category_scores_gemma":[0.005808147,0.0009159716,0.001415713,0.009803228,0.0004607056,0.002566045,0.002743003,0.002112566,0.2297173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00158318,"about_ca_system_score_gemma":0.00242268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0206405,"about_ca_topic_score_gemma":0.03432905,"domain_scores_codex":[0.9989306,0.0001452329,0.000140227,0.0003901326,0.0002121782,0.0001815564],"domain_scores_gemma":[0.9976653,0.0006351432,0.0001993857,0.0006373543,0.0006011683,0.0002617553],"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":[0.00003146502,0.00001250505,0.0004335902,0.0006501838,0.00001547442,0.00001817733,0.00002618989,0.0001275019,0.0001218915,0.0003752414,0.9965152,0.0016727],"study_design_scores_gemma":[0.00007028146,0.000009091657,0.001782745,0.0002118214,0.00001538006,0.00004499704,0.00008285319,0.0001828693,0.0001848519,0.0007873902,0.9966099,0.00001786782],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005305812,0.00003892413,0.00005287128,0.00004617047,0.00001580408,0.000006871999,0.9985423,0.0004873386,0.0007566026],"genre_scores_gemma":[0.00016895,0.00004143256,0.0002151764,0.00005657243,0.000004205776,0.00004429323,0.9988311,0.0001433719,0.0004949735],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8428245,"threshold_uncertainty_score":0.5258044,"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."}}