{"id":"W6893057227","doi":"10.5281/zenodo.14013741","title":"The Adaptive TEI Network: Antiracist, Decolonial, and Inclusive Markup Interventions","year":2024,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Politics; Schema (genetic algorithms); Markup language; Latin Americans; Appropriation; Outreach; The Internet; German","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005130296,0.0003957172,0.0003100705,0.000889242,0.005048548,0.002742793,0.00149736,0.001122333,0.01056744],"category_scores_gemma":[0.01445032,0.0001813195,0.0002465563,0.0004898457,0.004401847,0.003906307,0.007970417,0.00184348,0.00116502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002170091,"about_ca_system_score_gemma":0.003738241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00155628,"about_ca_topic_score_gemma":0.004276082,"domain_scores_codex":[0.9960011,0.00266852,0.00007604669,0.0003683561,0.0003984532,0.0004875281],"domain_scores_gemma":[0.9950981,0.002421873,0.0005059409,0.0005757084,0.0002488432,0.001149573],"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":[0.0008499181,0.00570208,0.00797675,0.0006496866,0.00005321034,0.001033971,0.3145383,0.000970599,0.003196848,0.1372568,0.02459998,0.5031718],"study_design_scores_gemma":[0.001006334,0.002885312,0.02522131,0.00192906,0.0001820433,0.0008671212,0.4669396,0.00834655,0.006320708,0.136009,0.3501378,0.0001550427],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8058905,0.0006207651,0.02174,0.01236403,0.0005820444,0.001254291,0.0000754049,0.0004078457,0.157065],"genre_scores_gemma":[0.9757388,0.0003469976,0.009544837,0.001060635,0.00006742263,0.001599023,0.00004770678,0.00006929879,0.01152522],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01056744,"threshold_uncertainty_score":0.03535157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0701107569952334,"score_gpt":0.271089566700459,"score_spread":0.2009788097052256,"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."}}