{"id":"W6962554318","doi":"10.15468/dl.pdr2mm","title":"Occurrence Download","year":2017,"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); Range (aeronautics); Ichthyology; 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":[0.001060767,0.001921899,0.001554958,0.005810284,0.0008982342,0.002647067,0.002739098,0.001896694,0.1784267],"category_scores_gemma":[0.00649146,0.0008679731,0.00120124,0.0110415,0.0004351346,0.002390921,0.002922658,0.001946003,0.2517379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00155866,"about_ca_system_score_gemma":0.002611492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02015809,"about_ca_topic_score_gemma":0.0363716,"domain_scores_codex":[0.9988258,0.0001525472,0.0001488828,0.000400543,0.0002746214,0.0001976608],"domain_scores_gemma":[0.9971349,0.0007247599,0.0002736291,0.0007609382,0.0007658681,0.0003399297],"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":[0.00002493101,0.000008327025,0.0003432714,0.0005090896,0.00001469812,0.00001145638,0.00001975142,0.00009792914,0.00009885283,0.0003444395,0.9971685,0.001358768],"study_design_scores_gemma":[0.00006178604,0.000007135337,0.001756585,0.0001942591,0.00001383033,0.00002996447,0.00006073151,0.0001082526,0.0001627496,0.000729236,0.9968593,0.00001612245],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003228562,0.00002532709,0.00003729988,0.00003103637,0.00001122791,0.000004708767,0.9989605,0.0003125372,0.0005851913],"genre_scores_gemma":[0.000133179,0.00003440309,0.0001685086,0.00004099041,0.000003669921,0.00003581684,0.9989863,0.0001370686,0.0004599633],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8215733,"threshold_uncertainty_score":0.5968968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02387106755018206,"score_gpt":0.2528130017232275,"score_spread":0.2289419341730454,"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."}}