{"id":"W6906083966","doi":"10.15468/dl.pjrwzr","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":[0.0009311864,0.002001722,0.001526591,0.004904598,0.0009582137,0.00248496,0.002558984,0.001903445,0.1712361],"category_scores_gemma":[0.006252128,0.0008899278,0.001187079,0.009753507,0.0004280266,0.002167526,0.002488792,0.001781447,0.2233072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001473745,"about_ca_system_score_gemma":0.002265734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02081249,"about_ca_topic_score_gemma":0.03249944,"domain_scores_codex":[0.9989535,0.0001396718,0.0001341385,0.0003805825,0.0002179431,0.0001742928],"domain_scores_gemma":[0.9975024,0.0007274881,0.0002405539,0.0006302389,0.0006196229,0.0002796721],"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":[0.00003162078,0.00001068673,0.0004000699,0.0005190716,0.00001385541,0.00001366199,0.00002069826,0.0001242471,0.0001086844,0.0003431976,0.9969856,0.001428701],"study_design_scores_gemma":[0.00007796487,0.00001007101,0.001897476,0.0001888308,0.00001507155,0.00003460066,0.00006489158,0.0001575279,0.0001851862,0.0007914288,0.9965586,0.00001831245],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000421786,0.00002468387,0.00003896424,0.00003326507,0.00001205281,0.000004971766,0.998847,0.0003758527,0.0006209853],"genre_scores_gemma":[0.0001684618,0.00003425248,0.0001923848,0.0000483972,0.000003844477,0.00004369189,0.9988421,0.0001627853,0.0005041513],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8287639,"threshold_uncertainty_score":0.5728418,"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."}}