{"id":"W6924820218","doi":"10.15468/dl.qqmkzh","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":[0.0009193636,0.001903861,0.00155957,0.005046753,0.0009647843,0.00259026,0.002629632,0.001915629,0.1812921],"category_scores_gemma":[0.006158975,0.0009204557,0.001159697,0.009634512,0.0004295705,0.002322031,0.002612913,0.001856979,0.2349095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001537324,"about_ca_system_score_gemma":0.002284638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01965758,"about_ca_topic_score_gemma":0.03180675,"domain_scores_codex":[0.9989686,0.0001396346,0.0001336333,0.0003738927,0.0002117432,0.0001725287],"domain_scores_gemma":[0.9976218,0.0006952626,0.0002284537,0.000584158,0.0006108027,0.0002594617],"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":[0.00002851765,0.00001052004,0.0003604774,0.0005770414,0.00001345022,0.00001397372,0.00002184842,0.0001083684,0.0001132769,0.000363362,0.996919,0.001470189],"study_design_scores_gemma":[0.00006397549,0.000008267742,0.00169211,0.0002010104,0.00001360303,0.00003362599,0.00006566531,0.0001311731,0.0001751663,0.0007311103,0.9968671,0.00001713835],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003839215,0.00002640345,0.00004159046,0.00003324886,0.00001205513,0.000005417747,0.998825,0.0003700674,0.0006479042],"genre_scores_gemma":[0.0001598234,0.0000386506,0.000207302,0.00004919145,0.000003874217,0.00004993266,0.9987683,0.0001730689,0.0005498694],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8187079,"threshold_uncertainty_score":0.6064826,"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."}}