{"id":"W74293027","doi":"","title":"Graph Data Representation in Oracle Database 10 g : Case Studies in Life Sciences.","year":2004,"lang":"en","type":"article","venue":"IEEE Data(base) Engineering Bulletin","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Oracle; Graph; Biological network; Biological data; Biological database; Graph database; Representation (politics); Data science; Theoretical computer science; Database; Software engineering; Bioinformatics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001015003,0.0001877628,0.0001952629,0.0001405319,0.00006869338,0.00003709888,0.0007604306,0.00009327316,0.00001977077],"category_scores_gemma":[0.0004453405,0.000192249,0.00002123622,0.0003092435,0.0001102989,0.00002836156,0.0007642136,0.0001754236,0.00003104755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002765498,"about_ca_system_score_gemma":0.00009374494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004212196,"about_ca_topic_score_gemma":0.000475472,"domain_scores_codex":[0.9984516,0.00002743595,0.0004409476,0.0005999646,0.0001401034,0.0003399361],"domain_scores_gemma":[0.9982449,0.00004049318,0.00008383048,0.001512976,0.00002831954,0.00008941267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001683543,0.0004292291,0.000796597,0.0005368783,0.0002087735,0.002651926,0.0005016343,0.742836,0.03477367,0.0002398421,0.2140092,0.002847896],"study_design_scores_gemma":[0.01941464,0.001002303,0.0009755994,0.002052324,0.0002620777,0.004035367,0.006007696,0.3254691,0.04910649,0.0003808904,0.5857218,0.005571755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9406775,0.01013551,0.04117849,0.001517385,0.001149194,0.0008762189,0.004167514,0.00008416357,0.000214028],"genre_scores_gemma":[0.9683518,0.001316722,0.02297218,0.0003331603,0.0002945708,0.00002689368,0.006620531,0.00003479902,0.00004929799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4173669,"threshold_uncertainty_score":0.7839686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06861363100284244,"score_gpt":0.3148171970292595,"score_spread":0.246203566026417,"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."}}