{"id":"W4241254018","doi":"10.23952/asvao.2.2020.2.01","title":"Editorial: A special issue dedicated to Hong-Kun Xu on the occasion of his 60th birthday, Part I","year":2020,"lang":"en","type":"editorial","venue":"Applied Set-Valued Analysis and Optimization","topic":"Chinese history and philosophy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Library science; Classics; History; Gerontology; Medicine; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.006216223,0.00486313,0.004352526,0.0053272,0.003750618,0.01012774,0.003247831,0.01100835,0.02686643],"category_scores_gemma":[0.02692507,0.001432483,0.00296039,0.002208208,0.002174787,0.004194893,0.001539581,0.01325867,0.01929034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002997689,"about_ca_system_score_gemma":0.003741513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001775626,"about_ca_topic_score_gemma":0.006133902,"domain_scores_codex":[0.9952578,0.0007461599,0.0006079382,0.0006949019,0.002357146,0.0003361611],"domain_scores_gemma":[0.9788033,0.006276581,0.001746051,0.0005455739,0.009041191,0.003587321],"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":[0.00003351393,0.00001039371,0.00001924622,0.0001152952,0.00001341272,0.00007102751,0.000005708943,0.00001772248,0.00004190671,0.0001143168,0.997483,0.002074554],"study_design_scores_gemma":[0.00009129123,0.00003894368,0.0004368362,0.0004226938,0.00007199794,0.0002483527,0.00004575952,0.0002112614,0.0001238031,0.0008517494,0.997431,0.00002621961],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0000183838,0.001550148,0.00006756946,0.01269058,0.9846022,0.0000166372,0.00004960904,0.00002897992,0.0009758513],"genre_scores_gemma":[0.0002310126,0.001858481,0.00007764158,0.008835698,0.9803508,0.0000242456,0.00004747751,0.00003119488,0.008543378],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.02686643,"threshold_uncertainty_score":0.08987719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142307732875381,"score_gpt":0.2681721421319601,"score_spread":0.253941368844422,"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."}}