{"id":"W6887301596","doi":"10.15468/dl.yyzmzt","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); Range (aeronautics); Download; Set (abstract data type); Identification (biology)","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":[0.0008701303,0.002100022,0.001604748,0.005169722,0.0009772675,0.002481775,0.002781421,0.001911295,0.1561666],"category_scores_gemma":[0.005213246,0.000940516,0.001173899,0.01022177,0.0004531259,0.00228577,0.002587088,0.001906354,0.2191876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001437791,"about_ca_system_score_gemma":0.002211143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0183777,"about_ca_topic_score_gemma":0.0328267,"domain_scores_codex":[0.9989837,0.0001350576,0.0001319144,0.000369,0.0002123818,0.0001679479],"domain_scores_gemma":[0.9977551,0.0005940401,0.0002207363,0.0006077502,0.0005565253,0.0002658716],"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":[0.00003589787,0.00001226661,0.0003903876,0.0006180303,0.00001624073,0.00001573951,0.00002371962,0.0001264573,0.0001460462,0.000403713,0.9966908,0.001520694],"study_design_scores_gemma":[0.0000744102,0.000009079267,0.001767962,0.0001739517,0.00001477827,0.00003822259,0.00006342041,0.0001262104,0.0001891637,0.0007633659,0.9967609,0.0000184724],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004339891,0.00002806636,0.00003958165,0.00002836683,0.00001162986,0.0000048117,0.9988764,0.0003284999,0.0006392752],"genre_scores_gemma":[0.0001455468,0.00003395347,0.000183478,0.00004182279,0.000003360388,0.00003704004,0.9989786,0.0001270793,0.0004491308],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8438334,"threshold_uncertainty_score":0.5224292,"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."}}