{"id":"W6887156971","doi":"10.15468/dl.puy7vf","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); Identification (biology); Data set","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":[0.0009600701,0.001983748,0.001608649,0.004820474,0.001015592,0.002591885,0.002883219,0.002057759,0.1634891],"category_scores_gemma":[0.005636609,0.000934191,0.001140151,0.009343578,0.0004600995,0.002438169,0.002629746,0.002034524,0.2277872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001467297,"about_ca_system_score_gemma":0.002258547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01959769,"about_ca_topic_score_gemma":0.03606389,"domain_scores_codex":[0.999003,0.0001366968,0.0001234895,0.0003607369,0.0002117949,0.0001643923],"domain_scores_gemma":[0.9976091,0.0006639227,0.00022464,0.0006455994,0.0005674717,0.0002891248],"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":[0.00002802831,0.00001140127,0.0003677684,0.0005107304,0.00001418886,0.00001496683,0.00002478614,0.0001168816,0.000116554,0.0003829238,0.9971283,0.001283356],"study_design_scores_gemma":[0.00007182018,0.000007416423,0.001768921,0.0001675024,0.00001304772,0.00003662504,0.00007282988,0.0001352726,0.000177011,0.0008579032,0.9966731,0.00001857007],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004171046,0.000023666,0.00004774563,0.00003348542,0.00001186816,0.000005085499,0.9988089,0.0003804395,0.0006471511],"genre_scores_gemma":[0.0001624315,0.00002972224,0.0002162652,0.00004534522,0.000003573006,0.00004253659,0.9988569,0.0001643338,0.0004789099],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8365109,"threshold_uncertainty_score":0.5469255,"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."}}