{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004118867,0.0003377622,0.0003500717,0.0001731703,0.0002733286,0.0004861581,0.003148614,0.0003057254,0.0009065161],"category_scores_gemma":[0.0001906835,0.0002829771,0.0002036826,0.0006227336,0.0001573329,0.004543642,0.001654074,0.0002207239,0.3892407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003831934,"about_ca_system_score_gemma":0.0002386229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002608503,"about_ca_topic_score_gemma":0.0000137515,"domain_scores_codex":[0.9977607,0.00009615746,0.0004890744,0.0004243543,0.0008245965,0.0004050843],"domain_scores_gemma":[0.9971155,0.00003259984,0.0004704408,0.001796372,0.0003508141,0.0002342876],"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":[0.000007701818,0.00002144094,0.000252526,0.00004776413,0.00004029408,0.000003254467,0.00001549479,0.000001320955,2.527103e-8,0.000001443468,0.9930514,0.006557357],"study_design_scores_gemma":[0.0002587311,0.00002272452,0.00004255675,0.00000348354,0.00003562542,0.00000570237,0.000009458238,9.843634e-7,0.000002618779,0.000004476452,0.9992713,0.0003423055],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001020704,0.00001320465,0.002379474,0.0004558189,0.0006558603,0.0001931654,0.9959902,0.0001786215,0.0001235059],"genre_scores_gemma":[0.000002842132,0.00005524257,0.00001951475,0.000748143,0.000001730859,0.000003031594,0.9991693,7.582782e-9,2.115279e-7],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3883342,"threshold_uncertainty_score":0.9999622,"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."}}