{"id":"W6962536987","doi":"10.15468/dl.q9mepj","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":[0.0009396837,0.002031292,0.001567319,0.004882221,0.0009565901,0.00248706,0.002649403,0.001995469,0.157309],"category_scores_gemma":[0.006117621,0.0008793813,0.001224923,0.009567968,0.0004296446,0.002102294,0.002431566,0.001812038,0.2082112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001517408,"about_ca_system_score_gemma":0.002324415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02070728,"about_ca_topic_score_gemma":0.03395759,"domain_scores_codex":[0.9989907,0.0001406225,0.0001278221,0.0003648187,0.0002134401,0.0001625898],"domain_scores_gemma":[0.9976543,0.000711272,0.0002219019,0.0005754571,0.0005862328,0.0002508757],"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":[0.00003376485,0.00001214495,0.000415628,0.0006381157,0.00001611405,0.00001598118,0.0000221258,0.0001375803,0.000129235,0.0003573843,0.9967086,0.001513402],"study_design_scores_gemma":[0.00008380718,0.00001103395,0.001951666,0.0002118746,0.00001715041,0.0000393535,0.00006813995,0.0001731546,0.0002019821,0.0008133238,0.9964089,0.00001956744],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004379937,0.00002956037,0.00004058289,0.00003456367,0.00001164589,0.000005431105,0.9988739,0.0003767622,0.0005837062],"genre_scores_gemma":[0.000171098,0.00003746838,0.0002068801,0.00004989321,0.000003679998,0.00004764295,0.998858,0.0001496644,0.0004757272],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.842691,"threshold_uncertainty_score":0.5262511,"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."}}