{"id":"W6887325560","doi":"10.15468/dl.yskmtt","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; Listing (finance); Matching (statistics); Range (aeronautics); Herbarium","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":[0.001123404,0.001951217,0.001593848,0.005739415,0.0008910652,0.002585402,0.002791419,0.001796743,0.2264935],"category_scores_gemma":[0.006249664,0.0009784428,0.001168386,0.009378784,0.0004222305,0.002443668,0.003150671,0.001841684,0.2867675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001594131,"about_ca_system_score_gemma":0.002443623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01838537,"about_ca_topic_score_gemma":0.03104278,"domain_scores_codex":[0.9990115,0.0001165057,0.0001213222,0.0003328952,0.0002291993,0.0001884522],"domain_scores_gemma":[0.9972218,0.0006918401,0.0002669913,0.000717554,0.0007494363,0.0003524305],"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":[0.00002703491,0.000007678013,0.0002769209,0.0005385212,0.00001255688,0.00001171322,0.00001766778,0.00007712244,0.0001229438,0.0003298313,0.9970799,0.001498036],"study_design_scores_gemma":[0.00006709512,0.000006802162,0.001634337,0.0002186955,0.00001297179,0.00002831632,0.00004903894,0.00008979406,0.0001966088,0.0006991769,0.9969811,0.00001599662],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002373174,0.00001870275,0.00003552748,0.00002652884,0.000009717054,0.00000558061,0.9988343,0.0003849444,0.0006609233],"genre_scores_gemma":[0.0001384305,0.00003436808,0.0002031843,0.00005207898,0.000003943694,0.00004881108,0.9987963,0.0002178457,0.0005049621],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7735065,"threshold_uncertainty_score":0.7576963,"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."}}