{"id":"W2995276428","doi":"10.7202/1065075ar","title":"ADAPTING WEB ELECTRONIC LIBRARIES TO ENGLISH STUDIES","year":2019,"lang":"en","type":"article","venue":"Surfaces","topic":"Digital Games and Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"World Wide Web; Computer science; Library science; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003359653,0.00007265515,0.0001387622,0.00002852702,0.00007571862,0.0001524797,0.0001763218,0.00003386227,0.000129136],"category_scores_gemma":[0.0005400958,0.00006294159,0.00003474555,0.0002149707,0.00009030537,0.0004417682,0.00007088767,0.0000679716,0.0002882243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004369768,"about_ca_system_score_gemma":0.000230306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004988203,"about_ca_topic_score_gemma":0.00120737,"domain_scores_codex":[0.9990672,0.00004010923,0.00009358794,0.0001605011,0.000231975,0.0004066246],"domain_scores_gemma":[0.9995185,0.0001848351,0.00003063025,0.00009378989,0.00008418557,0.00008805932],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005474794,0.00007591696,0.05559993,0.00007487369,0.0002109982,0.00000503912,0.4148844,0.0003180439,0.000849092,0.3765156,0.02532383,0.1260876],"study_design_scores_gemma":[0.00006392114,0.00005946197,0.0003075551,0.00002327868,0.000003538176,3.042691e-8,0.05756469,0.000004079726,0.0001603309,0.0007957315,0.940921,0.00009636376],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6667337,0.002234995,3.049852e-7,0.0006629776,0.0006265451,0.0001297874,0.00000196012,0.0001025624,0.3295071],"genre_scores_gemma":[0.9185076,0.0004075194,0.0001296892,0.0002188339,0.0001935188,0.000005266572,7.791049e-7,0.000007655298,0.08052918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9155972,"threshold_uncertainty_score":0.3704636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02216179218853145,"score_gpt":0.2879264954796104,"score_spread":0.2657647032910789,"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."}}