{"id":"W6887134938","doi":"10.15468/dl.mtvxrl","title":"Occurrence Download","year":2019,"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); Training set; UniProt","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":[0.0008894865,0.001741128,0.001531291,0.005248599,0.001100087,0.002964076,0.002794747,0.001946027,0.1770687],"category_scores_gemma":[0.006290871,0.0008996812,0.001289614,0.01097171,0.0004490164,0.002682237,0.00293282,0.002088006,0.2636212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001644508,"about_ca_system_score_gemma":0.002467685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02009635,"about_ca_topic_score_gemma":0.03517909,"domain_scores_codex":[0.9989492,0.0001397069,0.0001491556,0.0003721885,0.0002220323,0.0001676509],"domain_scores_gemma":[0.9975749,0.0006549902,0.0002139186,0.0006378303,0.000663636,0.0002547071],"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":[0.00002735016,0.000009755982,0.0004019004,0.0006680412,0.00001466212,0.00001576636,0.00003025402,0.000119658,0.0001102543,0.0004846171,0.9959744,0.002143397],"study_design_scores_gemma":[0.00003983227,0.000005302686,0.001219107,0.0001805892,0.00001043091,0.00002963818,0.00007044872,0.0001017626,0.0001202518,0.0006957162,0.9975138,0.00001322538],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003977332,0.0000359038,0.000059884,0.00004253585,0.00001496657,0.00000566247,0.9985129,0.0004111401,0.0008771687],"genre_scores_gemma":[0.0001607118,0.00005255824,0.0002832914,0.0000547584,0.000004228934,0.00004862261,0.9985319,0.0001815738,0.0006823658],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8229313,"threshold_uncertainty_score":0.5923536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"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."}}