{"id":"W6887175340","doi":"10.15468/dl.rwc2ba","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":[0.000958563,0.002114807,0.001533949,0.004698589,0.0009799014,0.002391268,0.002735035,0.002033814,0.1480543],"category_scores_gemma":[0.005837644,0.0009250794,0.001246734,0.009515945,0.0004560789,0.002151876,0.002514745,0.001869012,0.2077904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001488115,"about_ca_system_score_gemma":0.002330824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02096396,"about_ca_topic_score_gemma":0.0341098,"domain_scores_codex":[0.998944,0.0001463304,0.0001357073,0.0003791923,0.0002181569,0.0001765358],"domain_scores_gemma":[0.9975827,0.0006893124,0.0002301816,0.0006308025,0.0005946289,0.0002723996],"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":[0.00003599894,0.00001344229,0.0004197129,0.0005636312,0.00001527136,0.00001493781,0.00002200797,0.0001428936,0.0001344734,0.0003590446,0.9967849,0.001493731],"study_design_scores_gemma":[0.00008925929,0.00001217816,0.002048538,0.0001992937,0.0000166076,0.00003936268,0.00007162959,0.000175932,0.0002206292,0.0008187341,0.9962878,0.00002009529],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004896961,0.00002668484,0.00004059042,0.00003351031,0.00001235513,0.000005254973,0.9988669,0.0003722292,0.0005935107],"genre_scores_gemma":[0.0001539788,0.00003146923,0.0001867187,0.0000439851,0.000003216903,0.00003907548,0.9989797,0.0001307408,0.0004309743],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8519458,"threshold_uncertainty_score":0.4952908,"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."}}