{"id":"W6924546215","doi":"10.15468/dl.nvf57y","title":"Occurrence Download","year":2021,"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); Range (aeronautics); Download; Kingdom; Base (topology)","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":[0.0007886137,0.003061318,0.002335055,0.006218463,0.001300318,0.003435726,0.002609835,0.002573422,0.2884767],"category_scores_gemma":[0.005346194,0.001083967,0.001966828,0.009095247,0.0004205748,0.003836742,0.004061995,0.002272364,0.3568878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001513851,"about_ca_system_score_gemma":0.002769494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02381094,"about_ca_topic_score_gemma":0.03986115,"domain_scores_codex":[0.998811,0.0001473888,0.0001731788,0.0004215261,0.000242266,0.0002046386],"domain_scores_gemma":[0.9977475,0.0006158059,0.0001654153,0.0005752705,0.0005612401,0.0003347335],"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":[0.00006487106,0.00001994503,0.0002987976,0.0007581559,0.00001743638,0.00002684538,0.00003258191,0.0001408564,0.0001207854,0.0004892064,0.9944152,0.003615344],"study_design_scores_gemma":[0.00009118006,0.0000160639,0.001281041,0.0002058063,0.00001839868,0.00005860777,0.00009576095,0.0003474292,0.0001894713,0.001259183,0.9964102,0.00002685028],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000875022,0.0001021556,0.0001693074,0.00008284464,0.00004386815,0.00001885485,0.9944003,0.002552701,0.002542514],"genre_scores_gemma":[0.0003174574,0.0001081578,0.0007434935,0.0001275257,0.00001100246,0.00006943326,0.9965396,0.0005446914,0.001538673],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7115233,"threshold_uncertainty_score":0.9650506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01878725496536469,"score_gpt":0.2292776369319846,"score_spread":0.2104903819666199,"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."}}