{"id":"W6943761693","doi":"10.15468/dl.xstvbg","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":"Download; Matching (statistics); Range (aeronautics); Identification (biology)","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":[0.0009603524,0.002058209,0.001642364,0.005384355,0.0009929636,0.002478988,0.00286082,0.002085664,0.1534496],"category_scores_gemma":[0.005500012,0.0008899193,0.001195567,0.009950228,0.0004447639,0.002245209,0.002591538,0.001914747,0.2204327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001491579,"about_ca_system_score_gemma":0.002190971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01930321,"about_ca_topic_score_gemma":0.03253374,"domain_scores_codex":[0.9989337,0.0001374539,0.0001411584,0.0003641521,0.0002410516,0.0001824878],"domain_scores_gemma":[0.9977058,0.0006248974,0.0002240799,0.0006183453,0.0005564922,0.0002704137],"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":[0.00003236124,0.00001214173,0.0003766692,0.0005854011,0.00001609101,0.00001760758,0.00002291414,0.0001210598,0.0001506083,0.0003597611,0.9967672,0.001538276],"study_design_scores_gemma":[0.00007099858,0.000009181913,0.002031248,0.0001991167,0.00001619571,0.00004475532,0.0000679988,0.0001384783,0.0002260893,0.0006885306,0.9964883,0.00001926383],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004544443,0.00002983543,0.00004455347,0.00003130749,0.00001159094,0.000005267743,0.9988347,0.0003791887,0.00061816],"genre_scores_gemma":[0.0001506443,0.00003198571,0.0001704658,0.00004016474,0.000003307258,0.00003805551,0.9990158,0.0001283805,0.0004212428],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8465505,"threshold_uncertainty_score":0.5133399,"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."}}