{"id":"W6924601270","doi":"10.15468/dl.s8h6fh","title":"Occurrence Download","year":2018,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Lithobates; Range (aeronautics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006813469,0.0004891503,0.000453949,0.0001650803,0.0004606324,0.000652918,0.003425097,0.0004900203,0.0007125291],"category_scores_gemma":[0.0002798812,0.0004982112,0.0002545707,0.0008684823,0.0003858201,0.00273469,0.002810871,0.0004075259,0.1792369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006374892,"about_ca_system_score_gemma":0.0003614678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000485742,"about_ca_topic_score_gemma":0.00002175304,"domain_scores_codex":[0.996978,0.0001625756,0.0006532653,0.000642835,0.0009920843,0.0005712128],"domain_scores_gemma":[0.9965053,0.00005808957,0.0004819185,0.001915012,0.0007318731,0.000307857],"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":[0.00001214691,0.00006586777,0.0002892311,0.0001027058,0.00002434308,0.0000035837,0.00006567113,0.000009626075,1.371277e-8,9.956486e-7,0.9942904,0.005135406],"study_design_scores_gemma":[0.000309214,0.0001061542,0.0001551059,0.000002942011,0.00002269227,0.00001611268,0.00001727677,0.00002183712,0.000003123348,0.00002383583,0.998818,0.0005036752],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001009994,0.0000176643,0.00300009,0.0002815676,0.002125423,0.0004659019,0.9935195,0.0003768749,0.0001120084],"genre_scores_gemma":[0.000007912944,0.00002282018,0.0001813602,0.0006938347,0.000006664975,0.000004846159,0.9990824,1.757647e-8,9.463037e-8],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1785244,"threshold_uncertainty_score":0.999747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01668460768661365,"score_gpt":0.2227517949990997,"score_spread":0.206067187312486,"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."}}