{"id":"W6962093764","doi":"10.15468/dl.sj9mes","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":[0.0009309425,0.002067268,0.001539528,0.004996791,0.0009819944,0.002503095,0.002609537,0.001955228,0.1656383],"category_scores_gemma":[0.005835782,0.0008940396,0.001196626,0.009707853,0.0004413747,0.002133351,0.002543895,0.001797709,0.2253492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00144397,"about_ca_system_score_gemma":0.002267339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0198135,"about_ca_topic_score_gemma":0.03217624,"domain_scores_codex":[0.9989854,0.0001387409,0.0001264414,0.000366756,0.0002114113,0.000171276],"domain_scores_gemma":[0.9976472,0.0006855662,0.0002222487,0.0005913364,0.0005865116,0.0002670726],"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":[0.00003202501,0.00001203453,0.0003944395,0.0005485369,0.00001399021,0.00001480174,0.00002179466,0.0001232665,0.000126898,0.0003474111,0.9969035,0.001461386],"study_design_scores_gemma":[0.00007897452,0.00001117421,0.001923537,0.0001947127,0.00001558307,0.00003826516,0.00006926038,0.0001515953,0.000205246,0.0007682124,0.9965244,0.00001902673],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004803663,0.00002871477,0.00004037754,0.0000339615,0.00001258005,0.000005336018,0.9987996,0.0003885332,0.0006428942],"genre_scores_gemma":[0.0001650888,0.0000347551,0.0001898905,0.0000462556,0.000003765935,0.00004343311,0.998885,0.0001511597,0.0004805345],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8343617,"threshold_uncertainty_score":0.5541152,"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."}}