{"id":"W6943349121","doi":"10.15468/dl.mtf2bb","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":"Matching (statistics); Download; Alien; Range (aeronautics); 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":[0.0009797454,0.002039254,0.001536077,0.004885999,0.001005441,0.002534358,0.002658287,0.002037188,0.1510484],"category_scores_gemma":[0.006302719,0.0008983103,0.001215588,0.009775989,0.0004531695,0.002130537,0.002505909,0.001821793,0.2070905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001518549,"about_ca_system_score_gemma":0.002360137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0209141,"about_ca_topic_score_gemma":0.03303547,"domain_scores_codex":[0.99891,0.0001508287,0.0001406562,0.0003912802,0.0002276015,0.0001797311],"domain_scores_gemma":[0.9975069,0.0007326597,0.0002388815,0.0006260084,0.0006264154,0.0002691275],"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":[0.00003585683,0.00001313393,0.0004527587,0.0006045678,0.00001527376,0.00001639668,0.00002320232,0.0001375809,0.0001407703,0.0003904224,0.9966266,0.001543516],"study_design_scores_gemma":[0.00008125271,0.00001118332,0.001957207,0.0002050351,0.00001587544,0.00003916517,0.00007300873,0.0001605367,0.000214575,0.0008157718,0.9964069,0.00001957791],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004859522,0.0000287598,0.00004052604,0.00003596124,0.0000124543,0.000005445192,0.9988368,0.000375077,0.0006164588],"genre_scores_gemma":[0.0001720766,0.00003494325,0.0001970315,0.0000478435,0.000003643164,0.00004384839,0.9989147,0.0001383008,0.0004475194],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8489516,"threshold_uncertainty_score":0.5053072,"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."}}