{"id":"W6943420237","doi":"10.15468/dl.meex2d","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":"Matching (statistics); Download; Alien; Range (aeronautics); 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":[0.0009166411,0.001941622,0.001557059,0.004789061,0.0009569994,0.002501453,0.002621553,0.001890372,0.1686638],"category_scores_gemma":[0.006059902,0.0008912558,0.001164346,0.009606253,0.000423194,0.002207112,0.002441003,0.001817588,0.2185175],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001521662,"about_ca_system_score_gemma":0.002294297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02122901,"about_ca_topic_score_gemma":0.03460709,"domain_scores_codex":[0.9990232,0.0001319312,0.0001232981,0.0003561935,0.0002063828,0.0001590734],"domain_scores_gemma":[0.9977235,0.0006781303,0.0002200895,0.0005604559,0.0005713753,0.0002464843],"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":[0.00003088821,0.00001077953,0.0003907817,0.0006142128,0.00001476332,0.00001466511,0.00002292007,0.0001252604,0.0001215619,0.0003731501,0.9967815,0.001499544],"study_design_scores_gemma":[0.00007076914,0.000009139671,0.001774814,0.000201692,0.00001481817,0.00003440806,0.00006523627,0.0001414141,0.0001814469,0.0007675738,0.9967211,0.00001762134],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003973041,0.00002742495,0.00004162032,0.00003277251,0.00001126502,0.000005051039,0.9988722,0.0003532128,0.0006166647],"genre_scores_gemma":[0.0001632769,0.00003821954,0.0002055265,0.00004918515,0.000003608399,0.0000475511,0.998808,0.0001603187,0.0005243333],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8313362,"threshold_uncertainty_score":0.5642366,"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."}}