{"id":"W6887287953","doi":"10.15468/dl.ua9epq","title":"Occurrence Download","year":2023,"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); Identification (biology); Data set","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":[0.001003114,0.001986224,0.001590098,0.004656882,0.0009617043,0.002449567,0.002838964,0.002009331,0.1457115],"category_scores_gemma":[0.005749628,0.0009418619,0.00120179,0.009542074,0.0004539464,0.00221408,0.002516312,0.002046301,0.2022826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00160373,"about_ca_system_score_gemma":0.002315565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02405998,"about_ca_topic_score_gemma":0.03697707,"domain_scores_codex":[0.9990163,0.0001312929,0.0001278302,0.0003328558,0.0002234948,0.0001681924],"domain_scores_gemma":[0.9977398,0.0006314358,0.000209158,0.0006136437,0.0005433742,0.000262598],"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":[0.0000301051,0.00001159164,0.0003986048,0.0005123159,0.00001542462,0.00001611254,0.00002683289,0.0001470887,0.0001359142,0.0004187879,0.9968431,0.00144414],"study_design_scores_gemma":[0.0000739746,0.000007677078,0.001888364,0.0001839881,0.00001448088,0.00003908309,0.00007896477,0.0001738192,0.0002132272,0.0008168533,0.9964907,0.00001870829],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004502181,0.00002432667,0.00005143378,0.00003436239,0.0000116436,0.000005152493,0.9987898,0.0004368,0.0006013571],"genre_scores_gemma":[0.0001637072,0.00003028948,0.0002113556,0.00003991438,0.000002892654,0.00003935771,0.9989477,0.0001671275,0.0003977692],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8542885,"threshold_uncertainty_score":0.4874535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}