{"id":"W4308627330","doi":"10.1145/3548659.3561310","title":"Academic search engines: constraints, bugs, and recommendations","year":2022,"lang":"en","type":"article","venue":"","topic":"Open Source Software Innovations","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Queen's University; Queen's University Belfast","keywords":"Usability; Search analytics; Search engine; Computer science; Search engine optimization; Set (abstract data type); Snowball sampling; World Wide Web; Digital library; Information retrieval; Data science; Web search query; Human–computer interaction","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2165118,0.003265588,0.00520276,0.02317555,0.0039336,0.01604359,0.007050049,0.007192259,0.008892911],"category_scores_gemma":[0.7473133,0.002921152,0.004086979,0.02766825,0.00589256,0.03011304,0.005544275,0.005908876,0.002026908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01198499,"about_ca_system_score_gemma":0.03558913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03354832,"about_ca_topic_score_gemma":0.08919653,"domain_scores_codex":[0.7366598,0.1158131,0.07351065,0.009382872,0.05921123,0.005422283],"domain_scores_gemma":[0.1044424,0.7332807,0.05759572,0.01506068,0.08471105,0.004909405],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0007778602,0.0005193896,0.07039046,0.05609724,0.001551544,0.001531482,0.01161154,0.002360255,0.0008858519,0.02120083,0.2643816,0.568692],"study_design_scores_gemma":[0.00114393,0.0009035835,0.05124948,0.3204061,0.008567445,0.004042546,0.09285836,0.02341164,0.003725241,0.1159312,0.3761684,0.001592213],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07189205,0.1596746,0.07327749,0.6569158,0.008328764,0.006510425,0.005897451,0.003106829,0.01439657],"genre_scores_gemma":[0.2704522,0.1076289,0.4835652,0.1052512,0.004769763,0.01036786,0.008267685,0.00163791,0.008059299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9839564,"threshold_uncertainty_score":0.9661804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03160691654576168,"score_gpt":0.2993039281746542,"score_spread":0.2676970116288925,"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."}}