{"id":"W6906117175","doi":"10.15468/dl.rwywvd","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":[0.0009024045,0.002044699,0.001503001,0.004902436,0.00096893,0.002410386,0.002632992,0.001955359,0.1606128],"category_scores_gemma":[0.005859386,0.000892312,0.001183806,0.009790036,0.0004473438,0.002130274,0.002482212,0.001808207,0.2191023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482871,"about_ca_system_score_gemma":0.002274099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02137387,"about_ca_topic_score_gemma":0.03485395,"domain_scores_codex":[0.9989905,0.0001367131,0.0001262611,0.0003614937,0.0002138564,0.0001712192],"domain_scores_gemma":[0.9976447,0.0006683072,0.0002272005,0.0006082482,0.0005869822,0.0002644616],"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":[0.00003118818,0.00001135974,0.0004087914,0.0005280147,0.00001399278,0.00001480767,0.00002273492,0.0001369977,0.0001269695,0.0003716626,0.9968234,0.001510039],"study_design_scores_gemma":[0.00007092476,0.000009629613,0.00178056,0.0001769098,0.00001413705,0.00003528226,0.00006707655,0.0001556759,0.0001903942,0.000775421,0.9967061,0.00001794542],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004721669,0.00002682062,0.00004284742,0.00003312805,0.000012364,0.00000502729,0.9987895,0.0003926034,0.0006505109],"genre_scores_gemma":[0.0001680011,0.00003422239,0.0002058033,0.00004563627,0.000003607419,0.00004186514,0.9988511,0.0001581124,0.0004917248],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8393872,"threshold_uncertainty_score":0.5373032,"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."}}