{"id":"W6906169123","doi":"10.15468/dl.w563h4","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":"Matching (statistics); Download; Alien; Range (aeronautics); 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":[0.0009406574,0.002079687,0.001539527,0.005157966,0.0009909468,0.002497834,0.00265242,0.001939407,0.1683027],"category_scores_gemma":[0.006030755,0.0009082296,0.001191741,0.01033133,0.0004560531,0.002114655,0.002542966,0.001799521,0.2285166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476031,"about_ca_system_score_gemma":0.00234133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02087371,"about_ca_topic_score_gemma":0.03310994,"domain_scores_codex":[0.9989635,0.000139654,0.0001306347,0.0003702746,0.0002187211,0.0001771614],"domain_scores_gemma":[0.9975321,0.0007098961,0.0002386287,0.0006269102,0.0006153296,0.0002769495],"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":[0.00003226294,0.0000115939,0.0003905743,0.0005597192,0.00001392922,0.00001468907,0.00002227259,0.0001266742,0.0001273894,0.0003543368,0.996865,0.001481578],"study_design_scores_gemma":[0.00007634346,0.00001030653,0.001828286,0.0001902062,0.00001502512,0.00003606543,0.0000678858,0.0001405792,0.0002009396,0.0007480083,0.996668,0.00001845987],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004458379,0.00002672007,0.00003858015,0.00003138255,0.00001196018,0.000005032993,0.9988426,0.0003634443,0.0006355871],"genre_scores_gemma":[0.000158285,0.00003414136,0.0001883151,0.00004387944,0.000003599886,0.00004284336,0.9989027,0.0001523237,0.000473971],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8316973,"threshold_uncertainty_score":0.5630285,"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."}}