{"id":"W6962017648","doi":"10.15468/dl.ksec5s","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":[0.000952847,0.001964353,0.001558649,0.005015227,0.0009878878,0.002636077,0.00268903,0.001999378,0.1841923],"category_scores_gemma":[0.00617031,0.000917012,0.001198969,0.009673486,0.0004197165,0.002305155,0.002588579,0.001892093,0.2410007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001566534,"about_ca_system_score_gemma":0.002326247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01908759,"about_ca_topic_score_gemma":0.03129313,"domain_scores_codex":[0.9989367,0.0001455543,0.0001338041,0.0003866228,0.0002194294,0.0001778153],"domain_scores_gemma":[0.997563,0.0007168321,0.0002314749,0.0006064412,0.0006237783,0.0002586398],"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":[0.00002898409,0.00001077739,0.0003671767,0.0005664765,0.00001402082,0.00001392331,0.00002015396,0.0001102681,0.0001110501,0.0003602941,0.996958,0.001438812],"study_design_scores_gemma":[0.00006949203,0.000009025711,0.001765246,0.0002016195,0.00001479153,0.00003477915,0.00006375269,0.0001415483,0.0001881526,0.0007880098,0.9967052,0.00001827294],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003712687,0.00002643422,0.00003935308,0.00003389501,0.00001178282,0.000005250185,0.9988471,0.0003514914,0.0006475263],"genre_scores_gemma":[0.0001594581,0.00003780566,0.0001991444,0.0000508354,0.000003942571,0.00004931221,0.9987767,0.0001605319,0.0005621728],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8158077,"threshold_uncertainty_score":0.6161847,"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."}}