{"id":"W6906048911","doi":"10.15468/dl.vjqvcs","title":"Occurrence Download","year":2021,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Data set; Association rule learning","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":[0.0007081375,0.002786996,0.00202666,0.00587676,0.001464509,0.003926729,0.002866237,0.002693208,0.2948813],"category_scores_gemma":[0.006482171,0.001000293,0.001835704,0.01020954,0.0004294393,0.004283105,0.003549895,0.002312557,0.4451509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001660867,"about_ca_system_score_gemma":0.002261711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02297637,"about_ca_topic_score_gemma":0.0448074,"domain_scores_codex":[0.99875,0.0001408116,0.0001568439,0.0004365856,0.0003015221,0.0002142505],"domain_scores_gemma":[0.9974819,0.0005981654,0.000176621,0.0005864611,0.0008326395,0.0003243834],"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":[0.00003812746,0.00001107025,0.0003316619,0.0004824033,0.00001078259,0.00002317992,0.00001993769,0.00009664807,0.00008530977,0.0003486879,0.9955526,0.002999505],"study_design_scores_gemma":[0.00004751141,0.00001039341,0.001092442,0.0001587341,0.00001135116,0.00005617867,0.00007747911,0.0002597728,0.0001453873,0.001068897,0.9970534,0.00001852693],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008913534,0.0001205306,0.0001809071,0.0001031416,0.00004702647,0.00001304434,0.9938241,0.002329752,0.003292381],"genre_scores_gemma":[0.0003464033,0.0001020035,0.0005298529,0.0001199368,0.0000147102,0.00004389067,0.9964558,0.0005748261,0.001812419],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7051188,"threshold_uncertainty_score":0.9864761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01878725496536469,"score_gpt":0.2292776369319846,"score_spread":0.2104903819666199,"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."}}