{"id":"W7106788914","doi":"10.15468/dl.9vng3p","title":"Occurrence Download","year":2025,"lang":"","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Herbarium; Polygon (computer graphics); Data collection","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":[0.0008717364,0.00185003,0.00159258,0.005293733,0.001172625,0.002749634,0.002791325,0.002125256,0.1544036],"category_scores_gemma":[0.006496167,0.0008722566,0.001284067,0.01020111,0.0004139362,0.002551053,0.002584944,0.00193274,0.2141626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001877047,"about_ca_system_score_gemma":0.00273946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02812235,"about_ca_topic_score_gemma":0.04769092,"domain_scores_codex":[0.9988285,0.0001428563,0.0001514214,0.0004176545,0.0002613138,0.0001981705],"domain_scores_gemma":[0.9972747,0.0007292115,0.0002440657,0.0007030491,0.0007561031,0.0002929194],"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":[0.00003442873,0.00001174703,0.000503143,0.0005731222,0.00001499467,0.00001758561,0.00002398322,0.0001236579,0.0001191578,0.0003883566,0.9963663,0.001823566],"study_design_scores_gemma":[0.00006367587,0.000008878003,0.002036894,0.0001996074,0.00001384899,0.00004191231,0.00008813775,0.0001767685,0.0001911017,0.0007226898,0.996439,0.00001755392],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004941932,0.00002949997,0.00004762246,0.00003852684,0.00001359711,0.000005189104,0.9987407,0.0004351914,0.0006402821],"genre_scores_gemma":[0.0001724028,0.00003498397,0.0002179717,0.00004389211,0.000003849163,0.00003783462,0.9988329,0.0001379047,0.0005182674],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8455964,"threshold_uncertainty_score":0.5165315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01434536157882973,"score_gpt":0.2311093459842124,"score_spread":0.2167639844053826,"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."}}