{"id":"W6943238721","doi":"10.15468/dl.rby63g","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":[0.0009582863,0.00202713,0.001554802,0.005067275,0.0009832474,0.002544282,0.002691312,0.001969857,0.1716067],"category_scores_gemma":[0.006304353,0.0009434588,0.00121124,0.01032707,0.000445715,0.002226285,0.002496939,0.001830965,0.2258207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001503961,"about_ca_system_score_gemma":0.002330392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02089608,"about_ca_topic_score_gemma":0.03298818,"domain_scores_codex":[0.998924,0.0001476967,0.00014145,0.0003838333,0.0002243719,0.0001786466],"domain_scores_gemma":[0.9974052,0.0007640222,0.0002446111,0.0006548988,0.0006447729,0.0002864523],"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":[0.00003100941,0.00001127717,0.0003708123,0.0005064384,0.00001357678,0.00001344128,0.00002011314,0.0001263202,0.0001072787,0.0003377713,0.9970577,0.001404268],"study_design_scores_gemma":[0.00008042373,0.00001041162,0.001860147,0.0001861316,0.0000149274,0.00003495032,0.00006909645,0.0001597383,0.0001862151,0.0007921815,0.9965874,0.00001839774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000443335,0.00002468444,0.00003941957,0.00003321848,0.00001190366,0.000004983183,0.9988625,0.0003620244,0.0006170105],"genre_scores_gemma":[0.0001580112,0.00003221236,0.00018692,0.000043942,0.000003550577,0.00004125906,0.9989091,0.0001486014,0.0004763724],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8283932,"threshold_uncertainty_score":0.5740818,"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."}}