{"id":"W6961672876","doi":"10.15468/dl.vz23t5","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Engineering Education and Global Impact","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Alien; 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":[0.00102987,0.002111524,0.001560907,0.004773971,0.001055462,0.002585605,0.002917741,0.00229618,0.1348533],"category_scores_gemma":[0.006121548,0.0008931371,0.001357886,0.008625768,0.0004821391,0.002313646,0.002542753,0.002137418,0.2053688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001630413,"about_ca_system_score_gemma":0.002305727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02218165,"about_ca_topic_score_gemma":0.03637102,"domain_scores_codex":[0.9989334,0.0001558379,0.0001293234,0.0003781902,0.0002327223,0.0001705975],"domain_scores_gemma":[0.9975421,0.0007110334,0.0002110705,0.000670147,0.0005848075,0.0002807576],"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":[0.00002841117,0.00001295773,0.000392242,0.0004674541,0.00001412611,0.00001551955,0.00002213075,0.0001294602,0.00009597067,0.0003421312,0.9972352,0.001244494],"study_design_scores_gemma":[0.00008873268,0.00001012123,0.002043568,0.0001962963,0.00001566908,0.00004327675,0.00008241027,0.0002221981,0.0001948874,0.0008716678,0.996212,0.00001923925],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000528592,0.00003211994,0.00004933447,0.00004779386,0.00001489771,0.000007038886,0.9986999,0.0004584864,0.0006376099],"genre_scores_gemma":[0.0001718361,0.00003423571,0.0002023006,0.00005311084,0.000004229983,0.00004854937,0.9988855,0.0001428348,0.0004574539],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8651468,"threshold_uncertainty_score":0.4511291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02044912245186578,"score_gpt":0.273936464046113,"score_spread":0.2534873415942472,"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."}}