{"id":"W2358800480","doi":"","title":"Research on Chinese Query using Ajax Technology in PHP and Smarty Environment","year":2015,"lang":"en","type":"article","venue":"Computer Knowledge and Technology","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"La Cité Collégiale","funders":"","keywords":"Ajax; Computer science; Encoding (memory); Premise; Mode (computer interface); Database; Query expansion; Process (computing); Function (biology); Sargable; ENCODE; Web search query; Information retrieval; World Wide Web; Web application; Search engine; Operating system; Artificial intelligence","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":[0.002729156,0.0005256427,0.0006543888,0.001677782,0.001233176,0.003146577,0.001352005,0.0008055588,0.00391858],"category_scores_gemma":[0.004283146,0.0003432095,0.0008222712,0.004505361,0.001116177,0.01137914,0.001139762,0.0009559058,0.0006513387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001424948,"about_ca_system_score_gemma":0.002614612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01084248,"about_ca_topic_score_gemma":0.003565545,"domain_scores_codex":[0.9964769,0.0008549637,0.0002940591,0.0005546691,0.001470817,0.0003485224],"domain_scores_gemma":[0.9980299,0.0008371372,0.0001015768,0.0002150789,0.0007307499,0.0000855422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008011072,0.0004729005,0.009142115,0.0033161,0.0001307376,0.00129535,0.008357091,0.006919229,0.07247943,0.2733384,0.02892502,0.5948225],"study_design_scores_gemma":[0.0004322066,0.001369729,0.02103551,0.000520757,0.0007197325,0.006630562,0.01315319,0.3130283,0.160084,0.1092376,0.3731926,0.0005957106],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1632892,0.01990958,0.7372068,0.005998475,0.0005443122,0.000791614,0.0007941736,0.003468781,0.06799708],"genre_scores_gemma":[0.7430432,0.02123594,0.2052494,0.001602308,0.0006660278,0.0004110992,0.00181138,0.0004480006,0.02553263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01084248,"threshold_uncertainty_score":0.0215587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07195164697822673,"score_gpt":0.3837336647029454,"score_spread":0.3117820177247187,"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."}}