{"id":"W1565999497","doi":"10.16995/dscn.37","title":"Digital Humanities at Siberian Federal University","year":2015,"lang":"en","type":"article","venue":"Digital Studies / Le champ numérique","topic":"Library Science and Information","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital humanities; Scholarship; Digital scholarship; Humanities; Promotion (chess); Library science; Incentive; Political science; Computer science; Art; Politics; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.00009790336,0.0001607917,0.0001738658,0.00007857472,0.0004059582,0.0009493995,0.0006433025,0.00004169927,0.000002348705],"category_scores_gemma":[0.00005983445,0.0001456022,0.0000707143,0.0002720602,0.0002009004,0.01670988,0.001055205,0.00006937861,0.0002142516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001778972,"about_ca_system_score_gemma":0.0001150832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001091595,"about_ca_topic_score_gemma":0.00002317286,"domain_scores_codex":[0.9989718,0.00001622946,0.0001733007,0.0002564715,0.000281312,0.0003008506],"domain_scores_gemma":[0.9993313,0.00004214963,0.00008794637,0.0002668709,0.0001457116,0.000126002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007715819,0.0002235935,0.01356111,0.00006270842,0.0001855556,0.000158393,0.8219606,0.000233047,0.00002187268,0.03356185,0.09720607,0.032748],"study_design_scores_gemma":[0.0008038697,0.0003210224,0.0009352413,0.00002869999,6.618513e-8,0.00005163151,0.4464152,0.001268908,0.0004674303,0.01086817,0.5382544,0.0005853082],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5638155,0.0001602992,0.008489014,0.001990141,0.0005117,0.0001609927,0.00003370324,0.0003657262,0.424473],"genre_scores_gemma":[0.9802659,0.00002488667,0.00004980047,0.0003635879,0.00008098484,0.000001992584,0.00002813885,0.000005600892,0.01917916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4410484,"threshold_uncertainty_score":0.9970429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04277334331907143,"score_gpt":0.2147359622657168,"score_spread":0.1719626189466453,"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."}}