{"id":"W6943120932","doi":"10.15468/dl.mc4znn","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":[0.0009370123,0.002043088,0.001582466,0.005015378,0.0009701225,0.002525861,0.002608307,0.001916639,0.1757545],"category_scores_gemma":[0.006260681,0.000917296,0.001195491,0.01005383,0.0004398075,0.002164542,0.00252668,0.001808631,0.2265292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001489601,"about_ca_system_score_gemma":0.002264793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0213417,"about_ca_topic_score_gemma":0.03352382,"domain_scores_codex":[0.9989793,0.0001397034,0.0001279936,0.0003695566,0.0002120649,0.000171355],"domain_scores_gemma":[0.9975181,0.0007449815,0.0002405996,0.0006245175,0.0006002347,0.0002716416],"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":[0.00003214325,0.00001071413,0.0003889138,0.0005668688,0.00001467519,0.00001460949,0.00002290255,0.0001330924,0.0001155516,0.0003616712,0.9968694,0.001469423],"study_design_scores_gemma":[0.00007831822,0.00001006022,0.001853267,0.0001964065,0.00001562691,0.00003542405,0.00006795133,0.0001561415,0.000186847,0.0008303254,0.9965507,0.0000189283],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004114759,0.00002516259,0.00003967645,0.00003281351,0.00001139929,0.000004943452,0.9988626,0.0003756724,0.0006065989],"genre_scores_gemma":[0.0001655837,0.00003507893,0.0001968241,0.00004716841,0.000003682857,0.00004456587,0.9988411,0.0001673981,0.0004985793],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8242455,"threshold_uncertainty_score":0.5879573,"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."}}