{"id":"W6962236566","doi":"10.15468/dl.xqb2x6","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":"Download; Matching (statistics); Range (aeronautics); Polygon (computer graphics); Population","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":[0.000841153,0.002241446,0.00192199,0.006061275,0.001315355,0.003761216,0.003125339,0.002185934,0.2333251],"category_scores_gemma":[0.006750807,0.0009660693,0.001633654,0.0103711,0.0004061685,0.003838618,0.00357908,0.002079259,0.3573034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001653892,"about_ca_system_score_gemma":0.002484923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01986736,"about_ca_topic_score_gemma":0.03396221,"domain_scores_codex":[0.9987342,0.0001387667,0.0001701076,0.0004540128,0.0002948494,0.000208035],"domain_scores_gemma":[0.9974759,0.0005895955,0.0002028163,0.0006942476,0.000752819,0.0002845302],"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":[0.00003893895,0.00001126223,0.0003979101,0.000574367,0.00001423853,0.0000225287,0.00002488435,0.00009034033,0.0001044425,0.0003844104,0.9952936,0.003043085],"study_design_scores_gemma":[0.00004191461,0.000009441238,0.001169867,0.0001631234,0.00001184585,0.00005054106,0.00007418741,0.0001821441,0.0001611968,0.0007101176,0.9974092,0.00001640082],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006997369,0.00007661858,0.0001205532,0.00007692631,0.0000321854,0.000009596984,0.9963412,0.001714877,0.001557998],"genre_scores_gemma":[0.0002365687,0.00008073591,0.0004168919,0.00008862193,0.000008853151,0.00004472143,0.9975025,0.0004634923,0.001157624],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7666749,"threshold_uncertainty_score":0.7805504,"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."}}