{"id":"W7106798836","doi":"10.15468/dl.mrt8k3","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":"Charadrius; Matching (statistics); Download; Range (aeronautics); Polygon (computer graphics)","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":[0.0009530722,0.001812909,0.001676452,0.005312797,0.001073995,0.002876203,0.002778974,0.002063148,0.1963978],"category_scores_gemma":[0.007011477,0.000943142,0.001161554,0.01014194,0.0003945296,0.002578536,0.002807694,0.001946814,0.2536988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001737597,"about_ca_system_score_gemma":0.0024995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02155689,"about_ca_topic_score_gemma":0.03393995,"domain_scores_codex":[0.9988514,0.0001382381,0.0001556473,0.0004053637,0.0002560925,0.0001932573],"domain_scores_gemma":[0.9973211,0.0007420933,0.0002551416,0.000670751,0.000724162,0.000286853],"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":[0.0000324141,0.00001008451,0.0004276956,0.0006415767,0.00001420802,0.00001643154,0.00002523893,0.0001083124,0.0001121172,0.0004190202,0.9963455,0.001847549],"study_design_scores_gemma":[0.00005910983,0.000007464187,0.001609192,0.0002073697,0.00001268955,0.0000362901,0.00007734141,0.0001393282,0.0001678482,0.0006698308,0.9969978,0.00001572573],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003693387,0.00002815972,0.00005058097,0.00003741655,0.00001183249,0.000004935164,0.9986841,0.0004557105,0.0006902909],"genre_scores_gemma":[0.0001723868,0.00004029597,0.000241556,0.0000525868,0.000003863408,0.00004289256,0.9986658,0.0001926503,0.0005878884],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8036022,"threshold_uncertainty_score":0.6570162,"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."}}