{"id":"W6887307769","doi":"10.15468/dl.tg65d7","title":"Occurrence Download","year":2025,"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; Range (aeronautics); Identification (biology); Data set","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":[0.001046764,0.001993512,0.001567764,0.005018987,0.0009593058,0.002598496,0.00282219,0.001971084,0.1588583],"category_scores_gemma":[0.006037908,0.0009239211,0.001223199,0.009586639,0.0004515148,0.002253393,0.002671528,0.001892531,0.2293231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00157319,"about_ca_system_score_gemma":0.002324645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01963363,"about_ca_topic_score_gemma":0.03174637,"domain_scores_codex":[0.9988856,0.0001551803,0.0001473154,0.0003827532,0.0002439346,0.0001851763],"domain_scores_gemma":[0.9975408,0.0006294684,0.0002368311,0.0006963973,0.0006077173,0.0002887994],"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":[0.00003164263,0.00001062807,0.0003406029,0.0005372951,0.00001594304,0.00001395976,0.00002153576,0.0001098204,0.0001197653,0.0003760801,0.9969867,0.001436076],"study_design_scores_gemma":[0.00006782766,0.000007596485,0.001680539,0.0001685922,0.00001356187,0.00003404602,0.00005791772,0.0001202972,0.0001942503,0.0007626417,0.9968766,0.00001617148],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000390631,0.00002766032,0.00004183168,0.00003366801,0.00001098433,0.000005277906,0.9988212,0.000389108,0.0006312141],"genre_scores_gemma":[0.0001536835,0.00003170646,0.0001752424,0.0000467501,0.000003341925,0.00003788181,0.9989777,0.0001443936,0.000429329],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8411417,"threshold_uncertainty_score":0.531434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01437393559742932,"score_gpt":0.2320798631925623,"score_spread":0.217705927595133,"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."}}