{"id":"W6962412907","doi":"10.15468/dl.y7sjk2","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":[0.0008943165,0.002035863,0.001471272,0.004907389,0.0009514209,0.002385442,0.002585602,0.001902646,0.1601519],"category_scores_gemma":[0.005622803,0.0008773208,0.001191717,0.009685193,0.0004490238,0.002050349,0.002443267,0.001739367,0.2205824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001418632,"about_ca_system_score_gemma":0.002246834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02110179,"about_ca_topic_score_gemma":0.0342274,"domain_scores_codex":[0.9990292,0.0001319941,0.0001204643,0.0003490807,0.000202284,0.0001668557],"domain_scores_gemma":[0.9977393,0.0006441307,0.0002161619,0.0005785741,0.000566218,0.0002556203],"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":[0.00003260578,0.00001212273,0.0004291434,0.0005533119,0.00001451222,0.00001538005,0.00002296375,0.0001380773,0.0001344709,0.0003599444,0.9967327,0.001554751],"study_design_scores_gemma":[0.00007571316,0.00001065517,0.001970263,0.0001843338,0.00001513479,0.00003723221,0.00007022808,0.0001566308,0.0002038378,0.0007820654,0.9964752,0.00001878294],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005031524,0.00002799277,0.00004094726,0.0000327987,0.00001253502,0.000005234166,0.9987821,0.0003877632,0.0006603025],"genre_scores_gemma":[0.0001713099,0.00003385691,0.0001941457,0.0000448181,0.000003676168,0.00004202669,0.998881,0.0001494763,0.0004797423],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.839848,"threshold_uncertainty_score":0.5357616,"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."}}