{"id":"W6887301032","doi":"10.15468/dl.xgajq9","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); Alien; 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":[0.0009889177,0.001977811,0.001557639,0.004958423,0.001032992,0.002589609,0.002756417,0.002087308,0.1678947],"category_scores_gemma":[0.00601978,0.0008884549,0.001224043,0.009529248,0.0004635783,0.002312416,0.002605681,0.001998123,0.2435353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001536347,"about_ca_system_score_gemma":0.002287083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02052746,"about_ca_topic_score_gemma":0.03209258,"domain_scores_codex":[0.9990252,0.0001355688,0.0001206014,0.0003447517,0.0002114127,0.0001624646],"domain_scores_gemma":[0.9975393,0.0007094484,0.0002155134,0.0006497128,0.0006118452,0.0002743163],"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":[0.00002704706,0.00001119529,0.0003531892,0.0005220399,0.00001318559,0.00001490496,0.00002307123,0.0001181614,0.0001133713,0.0003405075,0.9970096,0.001453663],"study_design_scores_gemma":[0.00007095376,0.000008658119,0.001777336,0.0002029602,0.00001366639,0.00003551725,0.00007822723,0.0001486497,0.0001823529,0.0007287187,0.9967361,0.00001691711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004359816,0.00002832307,0.00004438303,0.00003895574,0.00001350916,0.000005876541,0.9987708,0.0003947631,0.0006597741],"genre_scores_gemma":[0.0001603513,0.00003483701,0.0001981513,0.00004818487,0.000003961461,0.00004797687,0.9988528,0.0001579568,0.0004957144],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8321053,"threshold_uncertainty_score":0.5616638,"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."}}