{"id":"W6924366076","doi":"10.15468/dl.n2aqys","title":"Occurrence Download","year":2022,"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); State (computer science); Order (exchange)","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":[0.001177131,0.00191663,0.001703507,0.005455136,0.001087873,0.002934713,0.003023149,0.001928439,0.1953413],"category_scores_gemma":[0.007012685,0.00100874,0.001175345,0.01094809,0.0004749326,0.002456333,0.002852141,0.002075517,0.2530238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0015267,"about_ca_system_score_gemma":0.002468857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01965679,"about_ca_topic_score_gemma":0.03267762,"domain_scores_codex":[0.9988371,0.0001576016,0.0001534041,0.0004043434,0.0002609052,0.0001867625],"domain_scores_gemma":[0.9971811,0.0008083947,0.0002574447,0.0007539125,0.0006839372,0.0003152979],"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":[0.00002639345,0.00000951842,0.0003239656,0.00052784,0.0000141612,0.00001377732,0.0000251273,0.00009896595,0.000108227,0.0003969997,0.9971288,0.001326259],"study_design_scores_gemma":[0.00005904977,0.000006181618,0.00144958,0.000179435,0.00001329987,0.00003254501,0.00006981326,0.0001050156,0.0001686894,0.0007737228,0.9971263,0.00001642252],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003463859,0.00002398842,0.00005196319,0.00003364121,0.00001209099,0.000005146657,0.998744,0.000397945,0.0006965101],"genre_scores_gemma":[0.0001530992,0.00003449497,0.0002190904,0.0000448359,0.000003587161,0.00004636174,0.9987586,0.0002163078,0.0005237429],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8046587,"threshold_uncertainty_score":0.6534817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}