{"id":"W4387091631","doi":"10.54590/pop.2023.010","title":"Why DHSI-East?: On Regional, National, and International Digital Humanities Training","year":2023,"lang":"en","type":"article","venue":"Pop! Public Open Participatory","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital humanities; Situated; Training (meteorology); Humanities; Library science; Geography; Art; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009011295,0.0004294266,0.0004433108,0.0008922997,0.0245086,0.01218938,0.002796549,0.003391309,0.01578981],"category_scores_gemma":[0.007491579,0.0004212056,0.0002611144,0.002246041,0.01161562,0.004507961,0.01446419,0.008872161,0.002219023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06738488,"about_ca_system_score_gemma":0.1463001,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8661621,"about_ca_topic_score_gemma":0.9676883,"domain_scores_codex":[0.9907064,0.001233746,0.0001248853,0.0005006199,0.001828884,0.005605519],"domain_scores_gemma":[0.9837855,0.001381066,0.0003523084,0.0003295424,0.003213757,0.01093783],"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":[0.0001869221,0.000246015,0.01790932,0.0008293099,0.00001951991,0.001193565,0.2261811,0.000296365,0.003121051,0.1311987,0.4481177,0.1707004],"study_design_scores_gemma":[0.000009783948,0.00002592705,0.01184859,0.000487129,0.000006380967,0.0001014541,0.3013677,0.00006432997,0.00042962,0.002047847,0.6835736,0.00003760657],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1658634,0.01834725,0.003982379,0.5172524,0.01108989,0.0004776716,0.001203842,0.0004962297,0.2812868],"genre_scores_gemma":[0.7362296,0.01094718,0.005056522,0.06335177,0.001200501,0.0003164278,0.0008073951,0.0005623249,0.1815283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9878106,"threshold_uncertainty_score":0.4889138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5942321177664872,"score_gpt":0.36626763514153,"score_spread":0.2279644826249572,"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."}}