{"id":"W6887075088","doi":"10.15468/dl.mgnnud","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":[0.0009532529,0.002039649,0.001542768,0.00487221,0.0009630325,0.002513863,0.002641778,0.001949112,0.169454],"category_scores_gemma":[0.006268052,0.0009095815,0.001232028,0.00990639,0.0004435086,0.002150186,0.002545811,0.001838419,0.2275606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001478087,"about_ca_system_score_gemma":0.002306914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02114576,"about_ca_topic_score_gemma":0.03367944,"domain_scores_codex":[0.9989271,0.0001469346,0.0001356221,0.0003912837,0.0002200971,0.000179038],"domain_scores_gemma":[0.9974526,0.0007477312,0.0002368268,0.0006592962,0.0006173668,0.0002862196],"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":[0.00003034802,0.0000110223,0.0003823412,0.0004862189,0.000013526,0.0000129598,0.00002002836,0.0001263528,0.0001040933,0.0003276855,0.9971035,0.001381938],"study_design_scores_gemma":[0.00008127753,0.00001090326,0.001928099,0.0001869639,0.00001561455,0.00003438791,0.00006829773,0.0001739424,0.0001915291,0.0008180059,0.9964718,0.00001931908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004332154,0.00002408325,0.0000398327,0.00003330325,0.00001223707,0.000005011915,0.998882,0.0003789875,0.0005810899],"genre_scores_gemma":[0.0001600316,0.00003225114,0.0001909228,0.00004611558,0.00000383334,0.00004449715,0.9988707,0.0001572007,0.0004945228],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.830546,"threshold_uncertainty_score":0.56688,"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."}}