{"id":"W6905808917","doi":"10.15468/dl.zyvtqp","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; Barcode; Matching (statistics); Range (aeronautics); Entomology; DNA barcoding","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":[0.001033388,0.002132712,0.001650593,0.005674262,0.001012134,0.002743654,0.002818894,0.002165286,0.1921593],"category_scores_gemma":[0.007309732,0.001022144,0.001407886,0.01022572,0.000403551,0.002678307,0.002927945,0.002001603,0.2450364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001717645,"about_ca_system_score_gemma":0.002439006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02126284,"about_ca_topic_score_gemma":0.0337892,"domain_scores_codex":[0.9987389,0.0001536961,0.0001811524,0.0004419322,0.0002733371,0.0002108891],"domain_scores_gemma":[0.9971094,0.0007983525,0.0002807188,0.0007534105,0.0007403602,0.0003177697],"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":[0.00003771359,0.00001191813,0.0004662266,0.000585835,0.00001553579,0.00001621964,0.00002311984,0.0001404639,0.0001105817,0.0003628832,0.9964916,0.001737786],"study_design_scores_gemma":[0.00008659837,0.00001066843,0.002004734,0.0002162385,0.00001506367,0.00004055653,0.00008088353,0.0002206816,0.000189731,0.000764452,0.9963516,0.00001880194],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003689061,0.00001991696,0.00004433925,0.00003096624,0.00001122405,0.000005449009,0.9989195,0.0004180297,0.0005137587],"genre_scores_gemma":[0.0001505456,0.00002969039,0.0002317504,0.00004092037,0.000003480956,0.00004660587,0.9988824,0.0001655833,0.0004490409],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8078407,"threshold_uncertainty_score":0.642837,"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."}}