{"id":"W4289921636","doi":"10.4000/jtei.3874","title":"Getting Along with Relational Databases","year":2021,"lang":"en","type":"article","venue":"Journal of the Text Encoding Initiative","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Metadata; Computer science; XML database; XML; Relational database; Information retrieval; Database; Relational database management system; World Wide Web","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":[],"consensus_categories":[],"category_scores_codex":[0.03320287,0.001878886,0.002660844,0.007158019,0.004205228,0.03152459,0.008641947,0.004169844,0.03553565],"category_scores_gemma":[0.08666973,0.002690044,0.003840411,0.01574019,0.004321154,0.05526925,0.01635804,0.01167237,0.04101753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003150394,"about_ca_system_score_gemma":0.005990336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005651836,"about_ca_topic_score_gemma":0.00247726,"domain_scores_codex":[0.9538491,0.01271262,0.008209474,0.005942127,0.01775561,0.001531125],"domain_scores_gemma":[0.9221316,0.02030417,0.002920544,0.03313618,0.01820548,0.003302012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001502029,0.00009084917,0.001354516,0.0009998363,0.0001899797,0.000420576,0.00179427,0.001904033,0.002037473,0.4909713,0.202661,0.297426],"study_design_scores_gemma":[0.00002464603,0.00002862454,0.000215159,0.0003526843,0.00004640412,0.0003312369,0.0004370057,0.00280066,0.001421875,0.2047136,0.7895566,0.00007138329],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001572638,0.01035513,0.8709724,0.02503578,0.00365892,0.0004896895,0.004619126,0.02979015,0.05350611],"genre_scores_gemma":[0.03345331,0.01818541,0.8675519,0.01219875,0.004916644,0.0006233292,0.01550718,0.009711774,0.03785178],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03553565,"threshold_uncertainty_score":0.1755956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05452991993167081,"score_gpt":0.2771809470700565,"score_spread":0.2226510271383857,"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."}}