{"id":"W6887343012","doi":"10.15468/dl.ye23hz","title":"Occurrence Download","year":2023,"lang":"en","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); Alien; Range (aeronautics); 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":[0.0009160838,0.00175417,0.001488844,0.005092773,0.0009646532,0.002712002,0.002598047,0.001909951,0.1838932],"category_scores_gemma":[0.006023439,0.0008684712,0.001164313,0.01017244,0.0004096664,0.002327169,0.002439135,0.001909474,0.2598339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001608373,"about_ca_system_score_gemma":0.002282235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02133558,"about_ca_topic_score_gemma":0.0352104,"domain_scores_codex":[0.9990041,0.0001414137,0.0001281112,0.0003444078,0.0002187304,0.0001632629],"domain_scores_gemma":[0.9976103,0.0006988582,0.0002157892,0.0005882457,0.0006276473,0.0002590866],"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":[0.00002363518,0.000009562873,0.0003301316,0.000492418,0.00001169503,0.00001285336,0.00002045216,0.00009641787,0.00009004043,0.000339843,0.9971189,0.001454014],"study_design_scores_gemma":[0.00005435565,0.000007257566,0.001628544,0.000200179,0.00001207252,0.00003240534,0.00007026903,0.0001245465,0.0001544802,0.0006909966,0.9970096,0.00001523316],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003704602,0.00002898254,0.00004136966,0.00003929226,0.00001200459,0.000005406383,0.9987805,0.0003264936,0.0007288973],"genre_scores_gemma":[0.0001537474,0.00004013125,0.0001914077,0.00004998827,0.000004061668,0.00004700292,0.9987389,0.000147097,0.0006276136],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8161068,"threshold_uncertainty_score":0.6151841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02365312271414112,"score_gpt":0.2392044605254057,"score_spread":0.2155513378112646,"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."}}