{"id":"W6924587253","doi":"10.15468/dl.ysnpf4","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":[0.0008375871,0.001983972,0.001451677,0.004642692,0.0008906803,0.002297122,0.002454799,0.001865899,0.1524835],"category_scores_gemma":[0.005303648,0.0008578573,0.001154514,0.009175252,0.0004151388,0.002051607,0.0023479,0.001727931,0.2060364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001386605,"about_ca_system_score_gemma":0.002138341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0193652,"about_ca_topic_score_gemma":0.03116656,"domain_scores_codex":[0.9990762,0.0001215991,0.0001177224,0.0003373057,0.0001868821,0.0001602917],"domain_scores_gemma":[0.9978786,0.0006037158,0.0002137753,0.0005357121,0.0005168028,0.0002515112],"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":[0.00003598068,0.00001252934,0.0004492863,0.0005747096,0.00001542406,0.00001569923,0.00002131929,0.0001479293,0.0001416594,0.0003530545,0.9966263,0.00160618],"study_design_scores_gemma":[0.0000841341,0.00001188533,0.002170156,0.0001900996,0.00001625676,0.00004098675,0.00006977231,0.0001781965,0.0002150286,0.0007633186,0.9962411,0.00001900996],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005116569,0.0000268257,0.00003893672,0.00003089622,0.00001224952,0.000004825934,0.9988986,0.0003567607,0.0005797205],"genre_scores_gemma":[0.0001739832,0.0000336208,0.000187606,0.00004335397,0.000003534871,0.00003833432,0.998938,0.0001325181,0.000449091],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8475165,"threshold_uncertainty_score":0.5101082,"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."}}