{"id":"W6931389591","doi":"10.5281/zenodo.5248501","title":"Eudendrium arbuscula Wright 1859","year":2012,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wright; Specific name; Index (typography); Species name; Correct name","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":[0.0001431059,0.000563757,0.0002315504,0.001145292,0.001037984,0.0003788925,0.0004239482,0.0005102081,0.01632648],"category_scores_gemma":[0.0003408189,0.0001970726,0.0001042805,0.000783531,0.0003441381,0.0007897655,0.0005921455,0.0003525151,0.006367548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003250089,"about_ca_system_score_gemma":0.0001450686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004508371,"about_ca_topic_score_gemma":0.008863924,"domain_scores_codex":[0.9998357,0.00002728585,0.00001747674,0.00004896277,0.00004999471,0.00002053403],"domain_scores_gemma":[0.9998766,0.00001558232,0.00004847404,0.00001303266,0.0000349304,0.00001132662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002261972,0.0001489727,0.02703298,0.0009170329,0.0000544481,0.001326384,0.001208427,0.0004475288,0.01948462,0.005568219,0.05360287,0.8899823],"study_design_scores_gemma":[0.00005772735,0.0001392249,0.2131637,0.0004339886,0.00006021317,0.003172014,0.0004910441,0.0003309887,0.002143566,0.001284198,0.7787009,0.00002239905],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.3024027,0.03847725,0.01286915,0.00133861,0.001524468,0.0005393377,0.006594446,0.00119658,0.6350575],"genre_scores_gemma":[0.9333473,0.008513903,0.00922754,0.0009621733,0.0004090237,0.0001270054,0.002750695,0.00008337079,0.04457898],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01632648,"threshold_uncertainty_score":0.05461752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02819945648880923,"score_gpt":0.2549779151213515,"score_spread":0.2267784586325423,"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."}}