{"id":"W6949911219","doi":"10.5281/zenodo.16537413","title":"Speyeria egleis subsp. kutoyisiks Kohler 2020","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Lepidoptera: Biology and Taxonomy","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subspecies; Range (aeronautics); Population; White (mutation); Front (military)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001031522,0.0005130199,0.0002856353,0.00207556,0.0009049122,0.0005213569,0.000460203,0.0003469888,0.04550401],"category_scores_gemma":[0.000211678,0.0002360269,0.0001976328,0.001298819,0.0002790837,0.001327744,0.0009980862,0.0006600709,0.01453865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005976186,"about_ca_system_score_gemma":0.0003478021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01153374,"about_ca_topic_score_gemma":0.03986489,"domain_scores_codex":[0.9998796,0.000003621522,0.00001447166,0.00004632715,0.00003534269,0.00002060019],"domain_scores_gemma":[0.999913,0.000008321342,0.00002545755,0.00001435812,0.00002512892,0.00001367946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002657164,0.0000833005,0.02046622,0.0006587544,0.00006987911,0.001100429,0.001248697,0.0006743098,0.01718996,0.002694095,0.05184644,0.9037021],"study_design_scores_gemma":[0.00002669002,0.0001123333,0.1718243,0.0004385461,0.00008830916,0.003352979,0.001358758,0.0004450068,0.003317802,0.001142586,0.8178581,0.00003439731],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.314956,0.01490131,0.008125517,0.0008665365,0.001437213,0.0005704431,0.0306156,0.001934699,0.6265927],"genre_scores_gemma":[0.6495386,0.01316881,0.02081793,0.0006300279,0.0003355268,0.0004703012,0.04034061,0.0003117128,0.2743865],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04550401,"threshold_uncertainty_score":0.152226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0291132389758962,"score_gpt":0.2295138411335811,"score_spread":0.2004006021576849,"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."}}