{"id":"W6887185576","doi":"10.15468/dl.scey7e","title":"Occurrence Download","year":2018,"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; Identification (biology)","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":[0.0009583959,0.0019052,0.001513257,0.005393418,0.0008465137,0.00248791,0.002585724,0.001846209,0.1612795],"category_scores_gemma":[0.005871923,0.0008234347,0.001147776,0.01040353,0.0004014261,0.002241765,0.002677134,0.001887502,0.2274278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001525581,"about_ca_system_score_gemma":0.002400573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02246554,"about_ca_topic_score_gemma":0.03824358,"domain_scores_codex":[0.9989519,0.0001358687,0.0001372413,0.0003524549,0.000241028,0.0001814981],"domain_scores_gemma":[0.9974477,0.0006312295,0.000255846,0.0006702529,0.0006714353,0.0003235039],"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":[0.00002640428,0.000009180607,0.0003503906,0.0004799695,0.00001502579,0.0000125777,0.00001908413,0.0001069645,0.00009577868,0.0003191165,0.9972259,0.001339553],"study_design_scores_gemma":[0.00006617483,0.000008079971,0.002042199,0.0001879814,0.00001452316,0.00003293955,0.00006067161,0.0001288834,0.0001611974,0.0006967305,0.9965848,0.00001573479],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000361207,0.0000252481,0.00003497458,0.00003193202,0.00001127887,0.000004852279,0.9989496,0.0003213195,0.0005847116],"genre_scores_gemma":[0.0001445031,0.0000320963,0.0001525139,0.00004128978,0.00000362386,0.00003290768,0.9990417,0.000117841,0.0004334196],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8387206,"threshold_uncertainty_score":0.5395335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01881883250631837,"score_gpt":0.2330296220854826,"score_spread":0.2142107895791642,"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."}}