{"id":"W6968951849","doi":"10.5281/zenodo.15021260","title":"Euura oehlkei","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Marine Ecology and Invasive Species","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Holotype; Type (biology); Margin (machine learning); Paratype; Single specimen","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005044531,0.0003458292,0.0001656125,0.000814617,0.0006863834,0.0003547095,0.0002665592,0.000448469,0.02205398],"category_scores_gemma":[0.0001561117,0.0001354084,0.0001261046,0.0004167215,0.0002788473,0.0005890334,0.0006152854,0.0003725517,0.007148733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002838016,"about_ca_system_score_gemma":0.0001297893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002242879,"about_ca_topic_score_gemma":0.005266615,"domain_scores_codex":[0.9999243,0.00001182789,0.000006486899,0.00002310659,0.00001851887,0.00001587748],"domain_scores_gemma":[0.999958,0.000008572883,0.00001114029,0.000006055789,0.00001132832,0.000004908642],"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":[0.0002347277,0.00009590205,0.01796323,0.0006744271,0.00003337361,0.001262946,0.0008210784,0.0004728872,0.02966923,0.007457785,0.02173216,0.9195823],"study_design_scores_gemma":[0.00004573629,0.000183462,0.2414415,0.0006772671,0.00007195918,0.006512643,0.001672307,0.0004956081,0.005529154,0.002158603,0.7411694,0.00004238262],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2470785,0.02047495,0.007495382,0.0005638702,0.0006852507,0.0003029632,0.002875287,0.0003367777,0.720187],"genre_scores_gemma":[0.8710127,0.006717111,0.006310208,0.0008229513,0.00009551196,0.0001227759,0.003181397,0.00004238641,0.111695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02205398,"threshold_uncertainty_score":0.07377791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01705015980453914,"score_gpt":0.2235777866273256,"score_spread":0.2065276268227865,"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."}}