{"id":"W4412520057","doi":"10.1002/asi.70006","title":"A study of search result aggregation approaches for the digital humanities","year":2025,"lang":"en","type":"article","venue":"Journal of the Association for Information Science and Technology","topic":"Information Retrieval and Search Behavior","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digital humanities; Computer science; Information retrieval; Data science; Humanities; Artificial intelligence; Library science; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.02341613,0.0005851542,0.0008605172,0.004689472,0.001930743,0.00423996,0.00143432,0.0006752122,0.001222929],"category_scores_gemma":[0.08564153,0.0005981563,0.0007291082,0.004677516,0.001667464,0.004584517,0.002471132,0.001155564,0.000169794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00225307,"about_ca_system_score_gemma":0.00169357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003892655,"about_ca_topic_score_gemma":0.003599544,"domain_scores_codex":[0.9792569,0.01489296,0.001110925,0.00111225,0.003247198,0.0003798041],"domain_scores_gemma":[0.8324382,0.1398626,0.01067685,0.00909606,0.006494185,0.00143203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003801369,0.005234226,0.1811187,0.002766278,0.0008689823,0.0006255041,0.1350667,0.01648087,0.05564157,0.03194434,0.002447803,0.5640038],"study_design_scores_gemma":[0.001240814,0.01064778,0.302286,0.001059446,0.001559176,0.00168923,0.09671871,0.4510444,0.05884529,0.04665498,0.02764778,0.0006064561],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9542252,0.0002334851,0.04119099,0.0002845295,0.00001679268,0.0006004569,0.00008356931,0.0003881293,0.00297681],"genre_scores_gemma":[0.9170038,0.00009451943,0.08192527,0.00005260397,0.00001330359,0.0004224227,0.00009025044,0.0000491951,0.0003486839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02341613,"threshold_uncertainty_score":0.1238378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04929919699916439,"score_gpt":0.2947339587881403,"score_spread":0.2454347617889759,"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."}}