{"id":"W6906000508","doi":"10.15468/dl.u7vy8q","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":"Download; Matching (statistics); Range (aeronautics); Set (abstract data type); Data set","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":[0.000957517,0.002066119,0.001396422,0.004512388,0.001069744,0.002406406,0.002932274,0.002036954,0.1170925],"category_scores_gemma":[0.005960769,0.0008619903,0.001319537,0.008367399,0.0004624352,0.002212989,0.002462832,0.002100974,0.1841818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001670807,"about_ca_system_score_gemma":0.002456638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02694335,"about_ca_topic_score_gemma":0.04373185,"domain_scores_codex":[0.9989367,0.0001406947,0.0001375976,0.0003542063,0.0002610564,0.0001698182],"domain_scores_gemma":[0.9977086,0.000605195,0.0001893625,0.0006539074,0.0005829469,0.0002600312],"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":[0.00002746417,0.00001254287,0.0003646695,0.0003743017,0.00001221904,0.00001596946,0.00002306007,0.0001182817,0.0001027157,0.0003620139,0.9972687,0.001317994],"study_design_scores_gemma":[0.00008471253,0.000009646461,0.002034431,0.0001645172,0.00001390216,0.00005058223,0.00009017576,0.0002565622,0.0002371636,0.0008817207,0.9961578,0.00001873804],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006733886,0.00003218312,0.00006899166,0.00005430054,0.00001565891,0.000008325909,0.9982535,0.0007101988,0.0007893529],"genre_scores_gemma":[0.0001791571,0.00002884266,0.0002339166,0.00004721365,0.000003440382,0.00004264446,0.9988958,0.0001557096,0.0004133425],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8829075,"threshold_uncertainty_score":0.3917134,"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."}}