{"id":"W6962089224","doi":"10.15468/dl.t98v6x","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":"Download; Matching (statistics); Range (aeronautics); State (computer science); Data set","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":[0.001118546,0.001974649,0.001577872,0.004879053,0.001078668,0.002669171,0.002996919,0.00208672,0.1632229],"category_scores_gemma":[0.006348043,0.0009718747,0.001170818,0.00958481,0.0004713853,0.002343723,0.00265287,0.002135155,0.2288511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001674462,"about_ca_system_score_gemma":0.002456332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02314173,"about_ca_topic_score_gemma":0.03865914,"domain_scores_codex":[0.9989145,0.0001444165,0.0001353184,0.0003767861,0.0002542697,0.0001747927],"domain_scores_gemma":[0.9974624,0.0007119576,0.0002298936,0.0006699567,0.0006435139,0.0002822623],"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":[0.00002691054,0.00001118086,0.0003553174,0.0004901597,0.00001368342,0.00001483459,0.00002476462,0.000115427,0.0001282477,0.0004048624,0.997062,0.001352649],"study_design_scores_gemma":[0.00006157356,0.000006826178,0.001648984,0.0001672929,0.00001275023,0.00003375746,0.00006966288,0.0001314441,0.0001954213,0.0007161808,0.9969389,0.00001714439],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004006998,0.00002365665,0.00005197888,0.00003573342,0.00001168808,0.000005277264,0.9987141,0.0004157159,0.000701726],"genre_scores_gemma":[0.0001562509,0.00002969744,0.0002173295,0.00004248683,0.000003102964,0.00004336888,0.9988375,0.0001821981,0.000488047],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8367772,"threshold_uncertainty_score":0.5460349,"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."}}