{"id":"W2406990242","doi":"10.4242/balisagevol3.muldner01","title":"XSAQCT: XML Queryable Compressor","year":2009,"lang":"en","type":"article","venue":"Balisage series on markup technologies","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; XML; Database; Gas compressor; Accounting; Software engineering; World Wide Web; Engineering; Business; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001346405,0.001293935,0.0007809827,0.001842504,0.0005806288,0.001678065,0.002465594,0.001164679,0.02046916],"category_scores_gemma":[0.005213108,0.0004043988,0.0005735611,0.002518273,0.001152419,0.003200038,0.001868785,0.001267541,0.00386169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009490289,"about_ca_system_score_gemma":0.001086254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005795692,"about_ca_topic_score_gemma":0.003264559,"domain_scores_codex":[0.9981465,0.0001641092,0.000194864,0.0001968326,0.00115315,0.0001445468],"domain_scores_gemma":[0.9977946,0.0006887353,0.0001443001,0.0005702553,0.0006746855,0.0001274055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004326212,0.0002482322,0.003341714,0.001983983,0.0001859597,0.00122843,0.0009822974,0.01263139,0.1566894,0.04886974,0.2373912,0.5321215],"study_design_scores_gemma":[0.0007468396,0.0008091026,0.002370463,0.0001993226,0.0001380444,0.001924884,0.0004163267,0.1879234,0.3274963,0.01942487,0.4582707,0.0002796349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03125957,0.001997197,0.693276,0.001206814,0.0005075391,0.001255209,0.01799428,0.2352185,0.01728481],"genre_scores_gemma":[0.3593138,0.00314429,0.5090036,0.002305544,0.0005295068,0.001605443,0.05203468,0.01766239,0.05440074],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02046916,"threshold_uncertainty_score":0.06847614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009228316138441564,"score_gpt":0.2297983960779826,"score_spread":0.220570079939541,"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."}}