{"id":"W7078285675","doi":"10.15468/dl.zbjqya","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","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":[0.0008220118,0.002235107,0.001545186,0.005332087,0.0009212089,0.002375315,0.002720905,0.001825878,0.1376512],"category_scores_gemma":[0.00527741,0.0008800249,0.001246778,0.009692201,0.0004210346,0.002199492,0.002532473,0.00180616,0.2019385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00153284,"about_ca_system_score_gemma":0.002293674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02207677,"about_ca_topic_score_gemma":0.03703411,"domain_scores_codex":[0.9989525,0.0001326735,0.0001415244,0.0003611183,0.0002364144,0.0001757962],"domain_scores_gemma":[0.9977314,0.0005524794,0.0002150827,0.0005860933,0.0006353331,0.0002796006],"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":[0.00003617703,0.00001162846,0.0003562912,0.0004986576,0.00001480871,0.00001466335,0.00001787177,0.0001196035,0.0001196883,0.0003430597,0.9970469,0.001420715],"study_design_scores_gemma":[0.00008646176,0.00001084343,0.00186822,0.000159554,0.00001507826,0.00004195177,0.00005773619,0.0001803703,0.0002157786,0.0007765909,0.9965689,0.00001843038],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005115395,0.00002965726,0.00004117503,0.00003320911,0.00001246654,0.000005485832,0.9987084,0.0004697446,0.0006487172],"genre_scores_gemma":[0.0001572789,0.00003410051,0.0001743481,0.00004247757,0.000003453374,0.00003150184,0.9989893,0.0001378865,0.0004296816],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8623489,"threshold_uncertainty_score":0.460489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0116959082794947,"score_gpt":0.2070852442648293,"score_spread":0.1953893359853346,"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."}}