{"id":"W7107956587","doi":"10.15468/dl.krnr39","title":"Occurrence Download","year":2025,"lang":"","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Norwegian; Matching (statistics); Arctic; Range (aeronautics)","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":["insufficient_payload"],"category_scores_codex":[0.0008270122,0.002446075,0.001900125,0.005587002,0.001247756,0.003803562,0.002854651,0.002144713,0.3275384],"category_scores_gemma":[0.006292969,0.0009748074,0.001665192,0.008860276,0.0003626072,0.00417426,0.003630854,0.002291067,0.4236688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001478577,"about_ca_system_score_gemma":0.002082801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01710583,"about_ca_topic_score_gemma":0.03171864,"domain_scores_codex":[0.9987835,0.0001374813,0.0001655887,0.0004406599,0.0002859561,0.0001867792],"domain_scores_gemma":[0.9976362,0.0005937498,0.0001649678,0.0006347051,0.0006754969,0.0002948288],"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":[0.00003706187,0.00001165816,0.0002414347,0.0003707404,0.00001060704,0.00001711037,0.00001718153,0.00008394608,0.0000746743,0.00036573,0.9961776,0.002592245],"study_design_scores_gemma":[0.00006407971,0.00001147298,0.001019034,0.0001255144,0.00001145999,0.00004472678,0.00006965704,0.0002753891,0.0001532831,0.001243659,0.9969637,0.00001817147],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007029844,0.00006981599,0.0001654653,0.00009185631,0.00004065326,0.00001436215,0.994269,0.00243439,0.002844148],"genre_scores_gemma":[0.0002671759,0.00007047857,0.0005523089,0.0001102662,0.00001199453,0.00005572268,0.996564,0.0005996875,0.001768423],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6724616,"threshold_uncertainty_score":0.9591848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434536157882973,"score_gpt":0.2311093459842124,"score_spread":0.2167639844053826,"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."}}