{"id":"W6887022811","doi":"10.15468/dl.ktw4xr","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); Identification (biology)","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":[0.0009762797,0.002070375,0.00156536,0.004932314,0.0009907552,0.002551375,0.002647305,0.002062021,0.1528945],"category_scores_gemma":[0.006376624,0.0009032242,0.00123646,0.009829303,0.0004567805,0.002127549,0.002524899,0.001816267,0.2082423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001504965,"about_ca_system_score_gemma":0.002360529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02092868,"about_ca_topic_score_gemma":0.03290503,"domain_scores_codex":[0.9989058,0.0001516485,0.0001425152,0.0003918176,0.0002270481,0.0001811783],"domain_scores_gemma":[0.9974679,0.0007493225,0.0002440562,0.0006324598,0.000628561,0.0002777646],"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":[0.00003602575,0.00001290937,0.0004504252,0.0006148609,0.00001561334,0.00001615339,0.00002246709,0.0001398047,0.0001331727,0.0003723411,0.9966696,0.001516752],"study_design_scores_gemma":[0.00008645338,0.00001188362,0.001995006,0.0002145316,0.00001670139,0.00003957562,0.00007186861,0.0001688891,0.000208768,0.0008242276,0.9963421,0.00002000216],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004734795,0.00002910295,0.00003826011,0.0000355645,0.00001252925,0.000005326151,0.9988762,0.0003681908,0.0005875268],"genre_scores_gemma":[0.0001699186,0.0000359431,0.0001897912,0.00004850619,0.000003692246,0.00004302495,0.998936,0.0001347975,0.0004383064],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8471056,"threshold_uncertainty_score":0.5114829,"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."}}