{"id":"W6962540219","doi":"10.15468/dl.ughnqq","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":[0.0009811224,0.001952383,0.001547677,0.004861287,0.001018435,0.002659239,0.002771832,0.002104455,0.1713394],"category_scores_gemma":[0.006439753,0.0009163159,0.001253836,0.009032008,0.0004397341,0.002581635,0.002627649,0.002080331,0.2366487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001576315,"about_ca_system_score_gemma":0.002312805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02053536,"about_ca_topic_score_gemma":0.03395431,"domain_scores_codex":[0.9989462,0.0001476749,0.0001268259,0.0003830973,0.0002271136,0.0001691341],"domain_scores_gemma":[0.9973701,0.0007774688,0.0002192251,0.0007116206,0.000641614,0.0002799194],"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":[0.00002492925,0.00001083428,0.00034568,0.0004934844,0.00001270296,0.00001376687,0.00002197814,0.0001157292,0.00009509956,0.000353701,0.9971237,0.001388398],"study_design_scores_gemma":[0.00006384732,0.000008136566,0.001638404,0.0001914069,0.00001305473,0.00003411229,0.0000748613,0.0001593206,0.0001682986,0.0008239775,0.9968072,0.00001747719],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004077089,0.00002780187,0.00004814492,0.0000444221,0.00001420138,0.000006137945,0.9987085,0.0004231361,0.0006870095],"genre_scores_gemma":[0.0001678022,0.00003737347,0.0002233266,0.00005553612,0.00000423624,0.00005055652,0.9987223,0.000173265,0.0005656225],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8286606,"threshold_uncertainty_score":0.5731875,"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."}}