{"id":"W6943593670","doi":"10.15468/dl.vh4xhh","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":[0.0009190689,0.002050887,0.001500314,0.004656286,0.0009512373,0.002398213,0.002628002,0.001973803,0.1484532],"category_scores_gemma":[0.005740405,0.0008906073,0.001238918,0.009262905,0.0004370754,0.002115601,0.002457279,0.001827133,0.2040139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0014396,"about_ca_system_score_gemma":0.002306862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01991024,"about_ca_topic_score_gemma":0.03272859,"domain_scores_codex":[0.9989793,0.0001361447,0.0001286626,0.0003718682,0.0002115131,0.0001725594],"domain_scores_gemma":[0.997663,0.0006605822,0.0002255015,0.0006137352,0.0005612584,0.0002759268],"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":[0.00003391181,0.00001256574,0.0004289335,0.0005210149,0.00001496166,0.00001468353,0.00001997508,0.0001398254,0.0001276774,0.0003422208,0.9968807,0.001463561],"study_design_scores_gemma":[0.00008619388,0.00001227688,0.002097277,0.0001892501,0.00001633307,0.00004106975,0.00006920009,0.0001822529,0.0002197037,0.000822343,0.9962441,0.00002001376],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005126946,0.00002707974,0.00003981071,0.00003486252,0.00001335783,0.000005205576,0.9988648,0.0003776889,0.0005860073],"genre_scores_gemma":[0.0001663656,0.00003254659,0.0001865518,0.00004616742,0.00000358754,0.00003892962,0.9989365,0.0001351835,0.0004542042],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8515468,"threshold_uncertainty_score":0.4966254,"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."}}