{"id":"W6905764214","doi":"10.15468/dl.bkj9jd","title":"Occurrence Download","year":2025,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Range (aeronautics); Set (abstract data type); Identification (biology); Download","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":[0.0009126667,0.002123686,0.001352808,0.004403285,0.001001523,0.002274867,0.002852717,0.001920146,0.1065471],"category_scores_gemma":[0.005811451,0.0008386201,0.001231882,0.008470485,0.0004568878,0.002168716,0.002433718,0.001967403,0.1674784],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001617786,"about_ca_system_score_gemma":0.002442101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02467731,"about_ca_topic_score_gemma":0.04304458,"domain_scores_codex":[0.9989312,0.0001383606,0.0001462926,0.0003618808,0.0002556288,0.0001664702],"domain_scores_gemma":[0.9976762,0.0005894352,0.0002102157,0.0006358786,0.000620615,0.0002676573],"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":[0.00003139052,0.0000138928,0.0003856585,0.0004081753,0.00001246503,0.00001559658,0.00002201279,0.0001300322,0.0001185639,0.000383174,0.9970192,0.001459828],"study_design_scores_gemma":[0.00008617585,0.00001082334,0.001907605,0.0001511578,0.00001309142,0.00004820281,0.00007824715,0.0002447382,0.0002341696,0.000877802,0.9963292,0.00001874555],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007209191,0.00003244068,0.00006363552,0.00004937936,0.00001572494,0.000007747803,0.9982815,0.0006712772,0.0008063158],"genre_scores_gemma":[0.000177201,0.00003138783,0.0002574755,0.00004699888,0.000003500007,0.00003964264,0.9988512,0.0001503016,0.0004422996],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8934529,"threshold_uncertainty_score":0.3564355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03761864349018661,"score_gpt":0.2888078212483628,"score_spread":0.2511891777581762,"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."}}