{"id":"W6924654265","doi":"10.15468/dl.r3n2p3","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":[0.0009229159,0.002026615,0.001494163,0.004784286,0.0009437973,0.002423148,0.002605754,0.001894498,0.1615577],"category_scores_gemma":[0.005807089,0.0008974476,0.001214442,0.009501559,0.000435648,0.002176996,0.002475977,0.001796164,0.2147535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001453191,"about_ca_system_score_gemma":0.002258853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.020092,"about_ca_topic_score_gemma":0.0321777,"domain_scores_codex":[0.9989981,0.0001347092,0.0001263934,0.0003669662,0.0002043144,0.0001694575],"domain_scores_gemma":[0.9976681,0.0006831806,0.0002222061,0.0005967648,0.0005650379,0.0002647297],"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":[0.00003378111,0.00001200599,0.0004203766,0.0005520656,0.00001525806,0.00001497799,0.00002150562,0.0001421358,0.0001304856,0.0003674373,0.9967436,0.001546393],"study_design_scores_gemma":[0.00007989294,0.00001111482,0.001990352,0.0001883764,0.00001611469,0.0000383445,0.00006860765,0.0001674967,0.0002090376,0.0008257548,0.9963856,0.00001931095],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004718927,0.00002593622,0.00004170742,0.00003250508,0.0000124459,0.000004981498,0.9988465,0.0003778543,0.0006109125],"genre_scores_gemma":[0.0001641186,0.00003289338,0.0001916667,0.00004516345,0.00000356694,0.00004018852,0.9989115,0.0001496553,0.0004611747],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8384423,"threshold_uncertainty_score":0.5404645,"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."}}