{"id":"W6943735732","doi":"10.15468/dl.wcjw5t","title":"Occurrence Download","year":2019,"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; Biodiversity; Herbarium; Barcode; Matching (statistics); Settlement (finance); Range (aeronautics)","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":[0.001012426,0.002114766,0.001844516,0.0064902,0.00120691,0.003280589,0.003142503,0.002221916,0.2174725],"category_scores_gemma":[0.007585331,0.00100501,0.001556856,0.01225933,0.0004253462,0.003313956,0.003294608,0.001938725,0.2904214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00167315,"about_ca_system_score_gemma":0.002172899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02099775,"about_ca_topic_score_gemma":0.03379903,"domain_scores_codex":[0.9986975,0.0001420781,0.000180011,0.0004852493,0.0002839752,0.0002111897],"domain_scores_gemma":[0.9970189,0.0008249381,0.0002570858,0.0007800605,0.0008241659,0.0002948755],"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":[0.00003713404,0.00001159285,0.0004806765,0.000690044,0.00001929447,0.000021099,0.00002633846,0.0001197143,0.0001341604,0.0003870694,0.9958639,0.002209017],"study_design_scores_gemma":[0.00006152194,0.000009862716,0.001850206,0.0002257791,0.00001731776,0.00004629539,0.00009339012,0.0001816889,0.0002047255,0.0008248054,0.9964641,0.00002031684],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004442895,0.00003024583,0.00006136852,0.00003465285,0.00001541201,0.000006004691,0.998455,0.0006232293,0.0007295272],"genre_scores_gemma":[0.0001712709,0.0000395037,0.0002618405,0.00005021328,0.000004592583,0.00004491904,0.9986506,0.0002417657,0.0005353775],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7825275,"threshold_uncertainty_score":0.727518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225412765836933,"score_gpt":0.2352696232258381,"score_spread":0.2127283466421448,"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."}}