{"id":"W6924870691","doi":"10.15468/dl.w4gn4k","title":"Occurrence Download","year":2024,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cervus elaphus; Cervus; Range (aeronautics); Matching (statistics); State (computer science)","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":[0.0008022189,0.002310082,0.001917301,0.006042001,0.001164677,0.003463197,0.002343544,0.002227247,0.3737121],"category_scores_gemma":[0.005612053,0.0008275695,0.001587514,0.008438546,0.0003346797,0.003086936,0.003173808,0.002036031,0.4398275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001528011,"about_ca_system_score_gemma":0.002392984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0203139,"about_ca_topic_score_gemma":0.03751387,"domain_scores_codex":[0.9989152,0.0001227059,0.0001529204,0.0003862021,0.0002364243,0.000186636],"domain_scores_gemma":[0.9973502,0.0006902216,0.0001918988,0.000644186,0.0007531901,0.0003703234],"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":[0.00004543793,0.00001769229,0.0002907012,0.0004921451,0.00001118337,0.00001702617,0.00002040599,0.00009972062,0.00009433123,0.0004340503,0.9944465,0.004030847],"study_design_scores_gemma":[0.00007837859,0.00001211025,0.001373398,0.0001736297,0.00001277592,0.00003906454,0.00006690134,0.0002866844,0.0001554858,0.001059541,0.9967189,0.00002301937],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005741023,0.00005570358,0.0001317352,0.0000715446,0.00003483382,0.00001442655,0.9954399,0.00154012,0.002654221],"genre_scores_gemma":[0.0002538299,0.00007332279,0.0006498596,0.0001200715,0.00001187211,0.00006734737,0.996538,0.0004081023,0.001877684],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6262879,"threshold_uncertainty_score":0.8933237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708767307206114,"score_gpt":0.2335971948231368,"score_spread":0.2165095217510757,"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."}}