{"id":"W6943616635","doi":"10.15468/dl.r8qpyz","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":[0.0009037899,0.002082179,0.001505865,0.004912739,0.0009635676,0.002377462,0.00260339,0.001967615,0.1552893],"category_scores_gemma":[0.005639049,0.0008698629,0.001190248,0.009464111,0.0004478701,0.002053347,0.002479316,0.001771614,0.2150753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001444649,"about_ca_system_score_gemma":0.00224927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02048164,"about_ca_topic_score_gemma":0.03308644,"domain_scores_codex":[0.9990213,0.0001340972,0.0001230473,0.0003517819,0.0002028389,0.0001669297],"domain_scores_gemma":[0.9977156,0.0006522907,0.0002218979,0.0005823323,0.0005682873,0.0002595744],"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":[0.00003350478,0.00001255049,0.0004384051,0.0005663622,0.00001454734,0.00001539648,0.00002302948,0.0001398745,0.0001346294,0.0003490084,0.9967174,0.001555338],"study_design_scores_gemma":[0.0000816365,0.00001158194,0.002044041,0.0001950939,0.00001579725,0.00003876519,0.00007416724,0.0001710157,0.0002114104,0.0007821454,0.9963548,0.00001971918],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005136001,0.0000285119,0.00004075251,0.00003350229,0.00001284079,0.000005468791,0.9988212,0.0003821412,0.0006241989],"genre_scores_gemma":[0.0001728272,0.00003386522,0.0001968739,0.00004443882,0.000003676398,0.00004453436,0.9989053,0.0001421345,0.0004564434],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8447107,"threshold_uncertainty_score":0.5194945,"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."}}