{"id":"W6887169463","doi":"10.15468/dl.rq95t4","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); Alien; 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":[0.0009664692,0.001949999,0.001569063,0.004955255,0.001003057,0.00260847,0.002689158,0.002085608,0.1667994],"category_scores_gemma":[0.00641162,0.0008731417,0.001253585,0.00928203,0.0004307597,0.002455927,0.002600685,0.00194709,0.2267844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001520317,"about_ca_system_score_gemma":0.002308531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02221651,"about_ca_topic_score_gemma":0.03490038,"domain_scores_codex":[0.9989717,0.0001419435,0.0001306779,0.0003680991,0.0002173066,0.0001703578],"domain_scores_gemma":[0.9973395,0.0008036512,0.0002298568,0.0006798783,0.0006596736,0.0002873572],"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":[0.00002765525,0.00001122394,0.0003966507,0.0005280393,0.00001366412,0.00001545264,0.00002281931,0.0001144662,0.00009933011,0.0003264646,0.9970216,0.001422633],"study_design_scores_gemma":[0.00007060154,0.000009119269,0.001975995,0.0002132388,0.00001467951,0.00003835692,0.0000826364,0.0001695044,0.0001770652,0.0007514986,0.9964793,0.00001810844],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004370094,0.00002730672,0.00004359995,0.00004136196,0.0000133986,0.000005774537,0.9987994,0.0004154153,0.0006100584],"genre_scores_gemma":[0.000172478,0.000036349,0.0002076585,0.00005206009,0.000004278119,0.00004632092,0.9988264,0.0001593986,0.0004950599],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8332006,"threshold_uncertainty_score":0.5579997,"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."}}