{"id":"W6924292091","doi":"10.15468/dl.naz2uj","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; Range (aeronautics); South carolina; R package","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":["insufficient_payload"],"category_scores_codex":[0.0007485724,0.002809404,0.002041326,0.007550292,0.001264226,0.003429306,0.002383839,0.002392681,0.3479706],"category_scores_gemma":[0.005354205,0.0008516796,0.001840634,0.01064922,0.0003939331,0.003165275,0.003578485,0.001980087,0.4672348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001501756,"about_ca_system_score_gemma":0.002395469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02248665,"about_ca_topic_score_gemma":0.04013379,"domain_scores_codex":[0.9988167,0.0001195121,0.0001544686,0.000418735,0.0002608949,0.0002297465],"domain_scores_gemma":[0.9975864,0.0005506069,0.0001852403,0.0006090157,0.0006708725,0.0003978436],"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":[0.00004418394,0.00001619382,0.000318687,0.0005393159,0.00001196165,0.00002074174,0.00002394467,0.0001109526,0.0001186429,0.0003810223,0.9945911,0.003823265],"study_design_scores_gemma":[0.00007039538,0.00001317012,0.001388912,0.0001828104,0.00001471113,0.00004739849,0.00008060924,0.0003034407,0.000150235,0.0009728567,0.9967518,0.00002366978],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000065134,0.00006650156,0.0001103001,0.00006306168,0.00003735162,0.00001158808,0.9953997,0.001765532,0.002480912],"genre_scores_gemma":[0.0002466883,0.00007564649,0.0005355488,0.0001046531,0.00001081886,0.000045959,0.9970515,0.0003940788,0.001535082],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6520294,"threshold_uncertainty_score":0.9300408,"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."}}