{"id":"W2159072246","doi":"","title":"Feminist Markup and Meaningful Text Analysis in Digital Literary Archives","year":2015,"lang":"en","type":"article","venue":"Lincoln (University of Nebraska)","topic":"Digital Humanities and Scholarship","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Markup language; Scholarship; Feminism; Digitization; Sociology; Computer science; Gender studies; World Wide Web; Political science; XML; Law","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01918973,0.0004865556,0.0004285439,0.006047817,0.007674988,0.01472593,0.001808735,0.00136446,0.005125569],"category_scores_gemma":[0.04543701,0.0004792568,0.0003806068,0.006652003,0.03137846,0.01413586,0.008198391,0.002403586,0.0007225309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005697746,"about_ca_system_score_gemma":0.003548218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00258532,"about_ca_topic_score_gemma":0.004705714,"domain_scores_codex":[0.9797555,0.01491389,0.0007548753,0.001227516,0.002973533,0.0003747462],"domain_scores_gemma":[0.9265546,0.05609754,0.003603125,0.01065466,0.002560455,0.0005297095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001131137,0.00005940268,0.003690291,0.0004839386,0.00001913511,0.000382425,0.4027002,0.0007263732,0.001832661,0.4875515,0.002810417,0.09963058],"study_design_scores_gemma":[0.00004052052,0.00009073019,0.004425752,0.001804128,0.0000354422,0.0009737649,0.3012728,0.002024712,0.01419493,0.2925459,0.3825089,0.00008234618],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4479723,0.008696038,0.2144438,0.02159096,0.0007703298,0.000554951,0.0006912015,0.0006949541,0.3045854],"genre_scores_gemma":[0.9212151,0.001915623,0.05778398,0.0007554858,0.0002177497,0.000427937,0.0001961115,0.0003683907,0.01711967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9852741,"threshold_uncertainty_score":0.1014862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03095654329734335,"score_gpt":0.1899755035819816,"score_spread":0.1590189602846383,"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."}}