{"id":"W6924738100","doi":"10.15468/dl.te7vs2","title":"Occurrence Download","year":2022,"lang":"en","type":"dataset","venue":"Global Biodiversity Information Facility","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Matching (statistics); Download; State (computer science); Range (aeronautics); Phragmites","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":[0.001155917,0.001941717,0.001706956,0.005473509,0.001068867,0.002853601,0.002992793,0.002021179,0.1853557],"category_scores_gemma":[0.006641881,0.001023546,0.001165446,0.01078629,0.0004696903,0.002476579,0.002811908,0.002087911,0.2399874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00160777,"about_ca_system_score_gemma":0.002438855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0208162,"about_ca_topic_score_gemma":0.03434951,"domain_scores_codex":[0.9988316,0.0001577075,0.0001538456,0.000406093,0.0002626834,0.0001881023],"domain_scores_gemma":[0.9972847,0.0007887367,0.0002555911,0.00071286,0.0006537205,0.0003044327],"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":[0.0000269144,0.000009820175,0.0003383024,0.0005472437,0.00001512527,0.00001435945,0.00002552643,0.0001102461,0.0001132712,0.0004002839,0.9970386,0.001360257],"study_design_scores_gemma":[0.00006240956,0.000006440499,0.001641571,0.0001929184,0.00001415953,0.00003412061,0.00007175859,0.0001186111,0.0001715338,0.0007449325,0.9969246,0.00001683167],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003359338,0.00002389141,0.00004736879,0.00003172308,0.00001080285,0.00000456503,0.9988727,0.0003468253,0.0006284961],"genre_scores_gemma":[0.0001457688,0.0000326761,0.0001992759,0.00004134363,0.000003190639,0.00004099303,0.9988901,0.0001767886,0.0004698017],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8146443,"threshold_uncertainty_score":0.6200765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01850871640220096,"score_gpt":0.2277224731265546,"score_spread":0.2092137567243537,"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."}}