{"id":"W6943465565","doi":"10.15468/dl.mmijrh","title":"Occurrence Download","year":2016,"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); Identification (biology); 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":[0.001069059,0.002062956,0.001559914,0.005097332,0.0009705931,0.002590384,0.00301595,0.002039168,0.1322411],"category_scores_gemma":[0.005936757,0.0009165062,0.001215757,0.009760994,0.0004606537,0.002336522,0.002668491,0.002084292,0.1892819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001672934,"about_ca_system_score_gemma":0.002475984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02319535,"about_ca_topic_score_gemma":0.03745171,"domain_scores_codex":[0.998929,0.0001452413,0.0001369926,0.0003650001,0.0002490892,0.0001747323],"domain_scores_gemma":[0.9976068,0.0006580814,0.0002315866,0.0006733572,0.0005447516,0.0002854308],"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":[0.00002949125,0.00001316217,0.0004226475,0.0004879349,0.00001602349,0.0000169784,0.00002693793,0.0001439668,0.000123518,0.000418674,0.9968004,0.001500143],"study_design_scores_gemma":[0.00007181949,0.000008416884,0.002031975,0.0001899815,0.00001498191,0.00004675853,0.00007885337,0.0001842307,0.0002195889,0.0008063558,0.9963289,0.0000181813],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005854469,0.00003279428,0.00005940559,0.00004070962,0.00001363765,0.000006114907,0.9985656,0.0005148824,0.0007083892],"genre_scores_gemma":[0.0001613333,0.00003023634,0.000196497,0.00003683661,0.00000280481,0.00003697535,0.9989852,0.0001443969,0.0004057137],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8677589,"threshold_uncertainty_score":0.4423904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01734962626846364,"score_gpt":0.227796013577581,"score_spread":0.2104463873091174,"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."}}