{"id":"W6943959920","doi":"10.15468/dl.m9p78w","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); State (computer science); Confidentiality","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":[0.0008727849,0.002113124,0.001566396,0.0045543,0.0009949997,0.002352833,0.003008245,0.00217538,0.1295826],"category_scores_gemma":[0.005103534,0.0008544087,0.001157186,0.008638509,0.0004571303,0.002189984,0.002439154,0.002050261,0.1916411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00159027,"about_ca_system_score_gemma":0.002199691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02229652,"about_ca_topic_score_gemma":0.03998678,"domain_scores_codex":[0.9990427,0.0001293413,0.0001176309,0.0003293313,0.0002210747,0.0001599222],"domain_scores_gemma":[0.9979604,0.0005609224,0.0001886787,0.0005179056,0.0005110426,0.0002609471],"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":[0.00002853062,0.00001395171,0.0003662294,0.0004724631,0.00001368602,0.00001678928,0.00002211709,0.0001459663,0.0001056305,0.0003219671,0.997075,0.001417674],"study_design_scores_gemma":[0.00008821666,0.0000101349,0.002000363,0.0001711208,0.00001411783,0.00004592057,0.00008050039,0.0002542573,0.000214005,0.0007858722,0.9963167,0.00001885454],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00006129087,0.00003197548,0.00005389797,0.00003966845,0.00001279663,0.000006887337,0.9986202,0.0004987165,0.0006745675],"genre_scores_gemma":[0.0001801194,0.00003029316,0.0002155523,0.00004082542,0.000003436673,0.00004267452,0.9989385,0.000133347,0.0004152941],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8704174,"threshold_uncertainty_score":0.4334969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089755290457145,"score_gpt":0.2074791423433098,"score_spread":0.1965815894387384,"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."}}