{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005964005,0.0001743271,0.0001456726,0.0002531066,0.001749644,0.0007480753,0.001751959,0.00006409315,0.003366568],"category_scores_gemma":[0.0004125842,0.0001797827,0.0000620662,0.0009302798,0.000125043,0.001495139,0.0017175,0.0002546138,0.01149457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001930446,"about_ca_system_score_gemma":0.000004028357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003355176,"about_ca_topic_score_gemma":4.799482e-8,"domain_scores_codex":[0.9979398,0.0003022499,0.0002427217,0.0004560731,0.0004623757,0.0005968123],"domain_scores_gemma":[0.9981614,0.00003034258,0.0001197187,0.0007604422,0.0006023581,0.0003257729],"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":[0.00005283416,0.00125704,0.00004581802,0.00008807871,0.0001620575,0.00004975207,0.008932754,0.004547963,0.007270052,0.2213779,0.1294255,0.6267903],"study_design_scores_gemma":[0.0004842864,0.00007385026,0.0009241034,0.00001164098,0.000006072339,0.0001802577,0.00008370986,0.01213441,0.001321142,0.0002709384,0.9842361,0.0002735383],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000502435,0.0001369358,0.9130831,0.0004846583,0.0003493893,0.0003153624,0.00002595224,0.001488733,0.08361348],"genre_scores_gemma":[0.7001637,0.0002456045,0.2855974,0.001211552,0.001168381,3.251931e-7,0.001028174,0.003599543,0.006985381],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8548106,"threshold_uncertainty_score":0.9995499,"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."}}