{"id":"W6924623583","doi":"10.15468/dl.vssddd","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); Alien; 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":[],"category_scores_codex":[0.001023884,0.001853529,0.001572643,0.004768492,0.0009831754,0.002584844,0.002662489,0.0020663,0.1558229],"category_scores_gemma":[0.006287694,0.0009034653,0.001215473,0.009083149,0.0004436469,0.002283909,0.002562206,0.001953113,0.2176956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001523919,"about_ca_system_score_gemma":0.002284836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02008309,"about_ca_topic_score_gemma":0.03116668,"domain_scores_codex":[0.9989895,0.0001445123,0.0001315245,0.0003546788,0.0002147732,0.0001650547],"domain_scores_gemma":[0.9974368,0.00077238,0.0002317792,0.000651075,0.0006218529,0.0002861646],"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":[0.00003053259,0.00001231552,0.0004266136,0.0006110646,0.00001562251,0.00001597919,0.00002474959,0.0001320826,0.0001280694,0.0003747017,0.9967498,0.001478628],"study_design_scores_gemma":[0.00007879979,0.00001008533,0.002170434,0.0002333835,0.00001589211,0.00003963141,0.00008499869,0.000167569,0.0001930497,0.0007620919,0.9962255,0.00001853445],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004575073,0.0000289227,0.00004320959,0.00004003963,0.00001358755,0.000005767991,0.9988592,0.0003635448,0.0005999585],"genre_scores_gemma":[0.0001711136,0.0000364234,0.0001953325,0.00004963938,0.000003964012,0.00004465157,0.9989054,0.0001386554,0.0004547908],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8441771,"threshold_uncertainty_score":0.5212796,"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."}}