{"id":"W2354970203","doi":"","title":"Optimizing Persistence Objects Query of Jdo Based on Objects Access Layer","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Layer (electronics); Factor (programming language); Persistence (discontinuity); Object (grammar); Filter (signal processing); Java; Index (typography); Persistent data structure; Database; Operating system; Artificial intelligence; Programming language; Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001315552,0.0004822674,0.0007570577,0.0005802708,0.000765715,0.001985119,0.001391067,0.0004625004,0.0009011144],"category_scores_gemma":[0.004095284,0.0003937308,0.0003674585,0.0006195215,0.0005964607,0.00311517,0.001110299,0.0006571409,0.0002094249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003491,"about_ca_system_score_gemma":0.001665246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01001728,"about_ca_topic_score_gemma":0.00691016,"domain_scores_codex":[0.9979267,0.0002192863,0.0001649243,0.0003354454,0.001001297,0.0003523233],"domain_scores_gemma":[0.9979495,0.0006906903,0.0001480197,0.0005734713,0.0004528366,0.0001854854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.005275745,0.00102016,0.04578279,0.0006494779,0.0002521196,0.000484394,0.0013673,0.03919557,0.3749295,0.02865726,0.01540068,0.4869849],"study_design_scores_gemma":[0.0007174638,0.0005891611,0.01082348,0.00002748883,0.0002111316,0.0002925949,0.000311956,0.7719226,0.1954592,0.005594842,0.01391829,0.0001316756],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6469227,0.001347654,0.3250498,0.0004781966,0.0001332023,0.0002945437,0.0002443493,0.01751186,0.008017709],"genre_scores_gemma":[0.8844068,0.0002355525,0.1099697,0.0001260517,0.00005867783,0.00007999082,0.0005323968,0.0006845616,0.003906164],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01001728,"threshold_uncertainty_score":0.01991796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02303782451289658,"score_gpt":0.2541541814132001,"score_spread":0.2311163569003035,"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."}}