{"id":"W6905480887","doi":"10.15468/dl.knmkek","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":"Download; Matching (statistics); Range (aeronautics); Alien; 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":[0.0009695058,0.001847368,0.001556102,0.004898167,0.001002259,0.002608745,0.002701653,0.002065468,0.1829674],"category_scores_gemma":[0.006259738,0.0008967884,0.00119274,0.008744864,0.0004423652,0.002409488,0.002643705,0.001959524,0.2394266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001520784,"about_ca_system_score_gemma":0.002243516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02049235,"about_ca_topic_score_gemma":0.03317196,"domain_scores_codex":[0.9990394,0.0001317507,0.0001173206,0.00034461,0.0002065049,0.0001604608],"domain_scores_gemma":[0.9975165,0.0007547251,0.0002168819,0.0006245874,0.0006075258,0.0002797873],"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":[0.00002626374,0.00001104568,0.0003753943,0.0005458232,0.00001339301,0.00001501548,0.00002328639,0.0001092119,0.0001072402,0.0003357113,0.9970386,0.001399099],"study_design_scores_gemma":[0.00007476637,0.000009057138,0.001942214,0.0002223216,0.00001498634,0.00003854759,0.00008297378,0.0001604487,0.0001783645,0.0007896225,0.9964683,0.00001839526],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000414339,0.00002702895,0.00004413995,0.00004098897,0.00001333246,0.000005984738,0.9987893,0.0003994979,0.0006383584],"genre_scores_gemma":[0.0001770207,0.00003610494,0.0002153269,0.00005483699,0.00000418915,0.00005150132,0.9987632,0.000169627,0.00052816],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8170326,"threshold_uncertainty_score":0.612087,"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."}}