{"id":"W6887327689","doi":"10.15468/dl.z7qcz3","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":[0.000903075,0.001978575,0.001452402,0.004778273,0.0009336371,0.002390293,0.002533012,0.001851851,0.1658227],"category_scores_gemma":[0.005794832,0.0008754001,0.001148699,0.00944027,0.0004276327,0.002119857,0.002482634,0.00172955,0.2229573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001414585,"about_ca_system_score_gemma":0.002227477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02018457,"about_ca_topic_score_gemma":0.03264537,"domain_scores_codex":[0.9990239,0.0001300087,0.0001262395,0.000348698,0.0002030683,0.0001681048],"domain_scores_gemma":[0.9976708,0.0006569024,0.0002234413,0.0005917703,0.0005866494,0.0002703176],"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":[0.00003177734,0.00001154282,0.0004098162,0.0005195373,0.00001332648,0.00001448606,0.00002111484,0.0001284404,0.0001211644,0.0003488718,0.9968988,0.001481163],"study_design_scores_gemma":[0.00007621283,0.00001051483,0.001950652,0.0001858351,0.00001449168,0.00003703818,0.00007029784,0.0001570071,0.0002013432,0.0007819805,0.9964963,0.00001842647],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000463844,0.00002410139,0.00004028214,0.00003174465,0.00001234703,0.000005064754,0.9988447,0.0003624385,0.0006329065],"genre_scores_gemma":[0.0001657139,0.0000316884,0.0001942926,0.00004432262,0.000003664544,0.0000410472,0.9988831,0.0001478165,0.000488438],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8341773,"threshold_uncertainty_score":0.5547323,"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."}}