{"id":"W6962425513","doi":"10.15468/dl.thpfm4","title":"Occurrence Download","year":2016,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Download; Matching (statistics); Range (aeronautics); Identification (biology); Order (exchange)","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":[0.0009863959,0.002062594,0.001662597,0.004758039,0.000959634,0.002408835,0.003156506,0.001983427,0.118354],"category_scores_gemma":[0.005403586,0.0008612925,0.001236051,0.009129376,0.0004561856,0.002012909,0.002435217,0.002111873,0.1829559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001639946,"about_ca_system_score_gemma":0.00247001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02073739,"about_ca_topic_score_gemma":0.03663154,"domain_scores_codex":[0.9989702,0.0001354838,0.0001259751,0.0003615729,0.0002397172,0.0001671478],"domain_scores_gemma":[0.9979275,0.0005062558,0.0001975412,0.0005849847,0.000517772,0.0002658882],"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":[0.00003067241,0.00001276485,0.0003948263,0.0004600283,0.0000163178,0.00001600096,0.00002073205,0.000138325,0.0001277476,0.0003715029,0.9970064,0.001404856],"study_design_scores_gemma":[0.00008889673,0.000008957982,0.002031428,0.0001609469,0.00001658716,0.00004806864,0.00006622115,0.0002091036,0.0002452288,0.000858332,0.9962479,0.00001819559],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005786936,0.00003399762,0.00005618463,0.00003597082,0.0000126215,0.00000676443,0.9986895,0.0004838781,0.0006232621],"genre_scores_gemma":[0.0001686788,0.00003085755,0.000201498,0.00003884381,0.000003129938,0.00004184829,0.999009,0.0001330084,0.000373016],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.881646,"threshold_uncertainty_score":0.3959336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01343996116406729,"score_gpt":0.2184511341112328,"score_spread":0.2050111729471655,"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."}}