{"id":"W4386315523","doi":"10.1093/dote/doad052.166","title":"355. DEVELOPMENT OF A CUSTOM RELATIONAL DATABASE FOR INTEGRATING CLINICAL AND RESEARCH DATA FOR THE STUDY FOR ESOPHAGEAL ADENOCARCINOMA","year":2023,"lang":"en","type":"article","venue":"Diseases of the Esophagus","topic":"Esophageal Cancer Research and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"","keywords":"Computer science; Relational database; Context (archaeology); Organoid; Data management; Data integrity; Database; Big data; Medicine; Data science; Data mining; Information retrieval","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":[0.007978539,0.0006735361,0.0007868988,0.002442011,0.0006534337,0.003920719,0.002598328,0.0005256818,0.01084047],"category_scores_gemma":[0.009789971,0.0007878983,0.00103322,0.002516026,0.0003571791,0.002681871,0.002213314,0.0008560524,0.00713491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009765704,"about_ca_system_score_gemma":0.002723902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003429979,"about_ca_topic_score_gemma":0.002495158,"domain_scores_codex":[0.9969687,0.0004727191,0.0008626443,0.0008439882,0.0006967828,0.0001552137],"domain_scores_gemma":[0.9944704,0.001481363,0.0004781398,0.001656433,0.001381314,0.0005324439],"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":[0.00296169,0.0006621907,0.02874794,0.001847414,0.0004426919,0.002733217,0.001677005,0.01146475,0.09494446,0.0274388,0.111729,0.7153509],"study_design_scores_gemma":[0.001272037,0.0009648386,0.03354997,0.0005464432,0.0006780552,0.004218538,0.000988498,0.1223506,0.1813544,0.02046299,0.6331539,0.0004596745],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0420274,0.0008442361,0.7012099,0.001186357,0.0003120531,0.003632987,0.07580807,0.1574298,0.01754924],"genre_scores_gemma":[0.1388184,0.0006901752,0.7164834,0.0006738997,0.0001334972,0.001676901,0.1242155,0.007524802,0.009783512],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01084047,"threshold_uncertainty_score":0.04219508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2913730443111429,"score_gpt":0.4963819400662584,"score_spread":0.2050088957551155,"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."}}