{"id":"W6887109503","doi":"10.15468/dl.prhxyt","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; Alien; Range (aeronautics); State (computer science)","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":[0.0009047997,0.00215167,0.0015433,0.004772418,0.001002796,0.002496629,0.002695544,0.002013101,0.1576042],"category_scores_gemma":[0.005617836,0.0008958439,0.00124538,0.009378005,0.0004337323,0.00221431,0.002491336,0.001845058,0.2258614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001473258,"about_ca_system_score_gemma":0.002278015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02059094,"about_ca_topic_score_gemma":0.03340352,"domain_scores_codex":[0.9989691,0.0001425832,0.0001252618,0.0003800486,0.0002116569,0.0001713976],"domain_scores_gemma":[0.9977306,0.0006440628,0.0002090695,0.0005877956,0.0005654484,0.0002631117],"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":[0.00003233134,0.00001220491,0.0003933906,0.0005090563,0.00001420113,0.0000144739,0.00001988441,0.0001255632,0.0001233158,0.000337269,0.9970197,0.001398625],"study_design_scores_gemma":[0.00007932847,0.00001168272,0.001974582,0.0001862759,0.0000161326,0.000040208,0.00006679865,0.0001769535,0.0002170546,0.0008163366,0.9963952,0.00001953217],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005014502,0.00003044282,0.00004197768,0.00003561921,0.00001297399,0.000005371397,0.9987655,0.000406458,0.0006515271],"genre_scores_gemma":[0.0001599576,0.000033867,0.0001800366,0.00004681948,0.000003679454,0.00004019525,0.9989197,0.0001422616,0.0004734641],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8423958,"threshold_uncertainty_score":0.5272386,"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."}}