{"id":"W6905713581","doi":"10.15468/dl.k7396n","title":"Occurrence Download","year":2022,"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); State (computer science); Identification (biology)","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":[0.0009904267,0.001991655,0.001513252,0.004882411,0.0009832934,0.002417683,0.002843319,0.002082204,0.1478771],"category_scores_gemma":[0.005638523,0.0008701187,0.001150618,0.009316154,0.0004623752,0.002229134,0.002517236,0.002020427,0.2099807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001547764,"about_ca_system_score_gemma":0.002237148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01981859,"about_ca_topic_score_gemma":0.03433844,"domain_scores_codex":[0.9990176,0.0001356792,0.0001219154,0.0003461975,0.0002162323,0.0001623471],"domain_scores_gemma":[0.9976839,0.0006584898,0.0002196539,0.0006109822,0.0005515397,0.0002754215],"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":[0.00002801218,0.0000125621,0.0003831366,0.0005157618,0.00001455368,0.00001530951,0.00002368194,0.0001375762,0.0001268271,0.0003775203,0.9969243,0.001440739],"study_design_scores_gemma":[0.00007031908,0.000008502814,0.00178423,0.0001812337,0.00001368756,0.00003779657,0.00007376423,0.0001632008,0.0002035218,0.0007459779,0.9967003,0.00001739595],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004865922,0.00002829794,0.00004780954,0.0000369497,0.00001322594,0.00000554517,0.9987778,0.0003859114,0.0006557153],"genre_scores_gemma":[0.0001682969,0.00003139934,0.0001984704,0.00004306376,0.000003518067,0.00004185403,0.9989184,0.0001392457,0.0004557248],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8521228,"threshold_uncertainty_score":0.4946983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}