{"id":"W6924105539","doi":"10.15468/dl.pr7yrs","title":"Occurrence Download","year":2023,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Advanced Clustering Algorithms Research","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); Confidentiality","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":[0.0009236685,0.002098419,0.001515656,0.004608701,0.001077556,0.002270599,0.003049358,0.002258058,0.09513448],"category_scores_gemma":[0.00497668,0.0008463798,0.001199697,0.008541177,0.0004644961,0.002115571,0.002434703,0.002139556,0.1618119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001703185,"about_ca_system_score_gemma":0.002229146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01948862,"about_ca_topic_score_gemma":0.03731531,"domain_scores_codex":[0.9990047,0.0001302088,0.0001303465,0.0003367793,0.0002357226,0.0001622612],"domain_scores_gemma":[0.9980018,0.0004906844,0.0001905932,0.000572797,0.0005047712,0.0002393625],"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":[0.00003192762,0.00001673904,0.000445739,0.0004818427,0.00001450053,0.00001902446,0.00002597299,0.0001591049,0.0001557006,0.0004118419,0.9966007,0.001636884],"study_design_scores_gemma":[0.00008329494,0.00001017116,0.002146641,0.0001744739,0.00001372887,0.00005647606,0.00009571566,0.0002625078,0.0002713916,0.0008325511,0.9960338,0.00001915239],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008903441,0.00003902548,0.0000709154,0.00004953697,0.00001639039,0.000008595937,0.9983125,0.0006063715,0.0008076368],"genre_scores_gemma":[0.0001952979,0.00003032887,0.0002744485,0.00004308711,0.000003268017,0.00004458974,0.9989026,0.0001184327,0.0003879377],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9048655,"threshold_uncertainty_score":0.3182566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02589576746805932,"score_gpt":0.2681033199922915,"score_spread":0.2422075525242322,"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."}}