{"id":"W6906318506","doi":"10.15468/dl.wr7ub3","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":"Download; Matching (statistics); Range (aeronautics); Robustness (evolution); Product (mathematics)","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":[],"consensus_categories":[],"category_scores_codex":[0.0009526504,0.001947834,0.001639786,0.004899646,0.0009593826,0.00255947,0.002798664,0.002036718,0.1597541],"category_scores_gemma":[0.005674182,0.0008919464,0.001112354,0.009847475,0.0004362887,0.002236375,0.002558866,0.001952503,0.2222154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001543398,"about_ca_system_score_gemma":0.002376673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02123963,"about_ca_topic_score_gemma":0.03707809,"domain_scores_codex":[0.9990059,0.0001349842,0.0001221837,0.0003506367,0.0002213909,0.0001649954],"domain_scores_gemma":[0.9977768,0.0006143384,0.0002126624,0.0005610993,0.000559425,0.0002757344],"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":[0.00002876177,0.00001030865,0.0003742866,0.0005712564,0.00001611559,0.0000140641,0.00002319125,0.0001193163,0.0001171921,0.0003925598,0.9969686,0.001364358],"study_design_scores_gemma":[0.00007071282,0.000007392157,0.001790742,0.0001959985,0.00001475415,0.00003377517,0.00006605866,0.0001256833,0.0001768026,0.0007503442,0.9967507,0.0000170454],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003697818,0.00002891607,0.00003873525,0.0000313307,0.000009939415,0.000004429397,0.9989464,0.0003203687,0.0005829942],"genre_scores_gemma":[0.0001539659,0.00003393154,0.0001678197,0.00004329616,0.000003049319,0.00003658197,0.9989961,0.0001325784,0.0004326979],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1597541,"threshold_uncertainty_score":0.5344306,"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."}}