{"id":"W6887132894","doi":"10.15468/dl.t4gm2n","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; Range (aeronautics); Alien; Set (abstract data type)","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":[0.0008897883,0.002076551,0.001512248,0.004992215,0.0009752496,0.002434221,0.002606802,0.001955686,0.1659172],"category_scores_gemma":[0.00567253,0.0008716646,0.001202242,0.009812031,0.0004492214,0.002106121,0.002504398,0.001773939,0.2231975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001463829,"about_ca_system_score_gemma":0.002249659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02077144,"about_ca_topic_score_gemma":0.03336004,"domain_scores_codex":[0.9990246,0.0001317573,0.0001227809,0.000347617,0.0002059455,0.0001672847],"domain_scores_gemma":[0.9977213,0.0006525592,0.0002209456,0.0005760937,0.0005698574,0.0002592357],"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":[0.00003293612,0.00001203441,0.0004163983,0.0005641218,0.00001410352,0.00001529547,0.0000229343,0.0001327936,0.0001275922,0.0003476823,0.9967738,0.001540366],"study_design_scores_gemma":[0.00007962903,0.00001102238,0.001931425,0.0001919998,0.00001506006,0.00003738371,0.00007147204,0.0001557834,0.0001978164,0.0007574814,0.9965323,0.00001863603],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004875002,0.00002832464,0.00003891241,0.0000332129,0.00001255451,0.000005344457,0.9988186,0.0003715857,0.0006427762],"genre_scores_gemma":[0.0001685629,0.00003521943,0.0001907225,0.0000456765,0.000003777357,0.00004390953,0.9988852,0.0001459023,0.0004809738],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8340828,"threshold_uncertainty_score":0.5550483,"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."}}