{"id":"W6943531762","doi":"10.15468/dl.mqsfgm","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":[0.0009287003,0.002062964,0.001541508,0.005023147,0.0009805836,0.002501565,0.002628576,0.001948954,0.1653576],"category_scores_gemma":[0.006108837,0.0008895861,0.001223739,0.01007188,0.0004469293,0.002200307,0.002562912,0.00182137,0.2239238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001497007,"about_ca_system_score_gemma":0.002303859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02112156,"about_ca_topic_score_gemma":0.03362465,"domain_scores_codex":[0.9989539,0.0001412684,0.0001343381,0.0003766882,0.0002169839,0.0001767852],"domain_scores_gemma":[0.9975383,0.0007037012,0.0002351973,0.0006318605,0.0006140771,0.000276844],"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":[0.00003149442,0.00001125063,0.0003994206,0.0005279278,0.0000139408,0.00001408275,0.00002156637,0.0001262088,0.0001129642,0.0003490318,0.9969318,0.001460369],"study_design_scores_gemma":[0.00007664262,0.00001043538,0.001898578,0.0001907854,0.00001506507,0.00003569445,0.0000696807,0.0001579504,0.0001891948,0.0007915619,0.9965455,0.00001876702],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004364688,0.00002538697,0.00003876599,0.00003248836,0.00001209959,0.00000498996,0.9988768,0.0003653554,0.0006004306],"genre_scores_gemma":[0.0001611065,0.00003370691,0.0001903661,0.00004534631,0.000003716481,0.00004241367,0.9988954,0.0001499036,0.0004779283],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8346424,"threshold_uncertainty_score":0.5531763,"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."}}