{"id":"W6924382596","doi":"10.15468/dl.kyxk69","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":[0.0009722002,0.001957521,0.001517884,0.004662128,0.001089949,0.002751954,0.002855026,0.002145997,0.1683414],"category_scores_gemma":[0.006310913,0.0009181931,0.001245278,0.008879405,0.0004418938,0.002672022,0.002631854,0.002160502,0.24463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001631412,"about_ca_system_score_gemma":0.002347277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02066517,"about_ca_topic_score_gemma":0.03572073,"domain_scores_codex":[0.9989269,0.0001567889,0.0001242072,0.0003928885,0.0002308954,0.0001682147],"domain_scores_gemma":[0.9974419,0.0007392623,0.0002083394,0.0007011018,0.0006383483,0.0002709818],"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":[0.00002481644,0.00001086828,0.0003306562,0.0004398056,0.00001199406,0.000013072,0.00002038584,0.0001063511,0.00008902598,0.0003535431,0.9972618,0.001337823],"study_design_scores_gemma":[0.00006177864,0.000008011353,0.001560802,0.000176441,0.00001228253,0.00003354438,0.00007234828,0.0001576144,0.0001638505,0.0008736179,0.9968624,0.00001730152],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004238483,0.00002927136,0.00005237887,0.00004707901,0.00001468402,0.000006281914,0.9985942,0.0004503255,0.0007634117],"genre_scores_gemma":[0.0001634295,0.00003639055,0.0002253607,0.00005620487,0.000004242766,0.00004922246,0.9986978,0.0001749562,0.0005924187],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8316585,"threshold_uncertainty_score":0.5631583,"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."}}