{"id":"W6905541035","doi":"10.15468/dl.ecf9k6","title":"Occurrence Download","year":2025,"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; Norwegian; Barcode; Matching (statistics); Lepidoptera genitalia; Range (aeronautics); Snow cover","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":[0.001041897,0.001955388,0.001607036,0.006317147,0.001080735,0.003082751,0.002756022,0.002027336,0.2046723],"category_scores_gemma":[0.007018213,0.0009761247,0.001340451,0.0114929,0.0004272053,0.00289826,0.00304627,0.001955053,0.2623001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001707001,"about_ca_system_score_gemma":0.00239593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01851762,"about_ca_topic_score_gemma":0.03109446,"domain_scores_codex":[0.9987412,0.0001555377,0.0001759806,0.0004590024,0.0002643017,0.0002039677],"domain_scores_gemma":[0.9972296,0.0007672191,0.0002563806,0.0007050167,0.0007239617,0.0003177196],"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":[0.00002755814,0.00000967915,0.0003672738,0.0006187208,0.00001418421,0.00001343995,0.00002413946,0.00009598045,0.00009343403,0.0003388346,0.9966626,0.001734181],"study_design_scores_gemma":[0.00005886882,0.000007862039,0.001615239,0.0002147546,0.00001318129,0.00003320177,0.00007760731,0.0001342203,0.0001433701,0.0006879837,0.9969977,0.00001594548],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003109591,0.00002609598,0.00004123001,0.00003482002,0.00001237369,0.000005579487,0.9988972,0.0003497755,0.000601813],"genre_scores_gemma":[0.0001449976,0.00003948167,0.0002199837,0.000050497,0.000004153186,0.00004797279,0.9987564,0.0001694122,0.0005669858],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7953277,"threshold_uncertainty_score":0.6846972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01437393559742932,"score_gpt":0.2320798631925623,"score_spread":0.217705927595133,"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."}}