{"id":"W3034627609","doi":"10.1158/1557-3265.advprecmed20-26","title":"Abstract 26: A novel electronic platform to improve clinical trial workflow and screening","year":2020,"lang":"en","type":"article","venue":"Clinical Cancer Research","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Clinical trial; Workflow; Computer science; Web application; Medicine; Password; Workload; Android (operating system); World Wide Web; Phone; Medical physics; Database; Pathology; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.06291292,0.0001799012,0.0006248025,0.0002504073,0.0004058619,0.001215964,0.002169746,0.0001847491,0.0005296989],"category_scores_gemma":[0.05185531,0.0001340685,0.0002809446,0.002072412,0.0005036806,0.0002945606,0.002413236,0.00182555,0.0008952442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000643131,"about_ca_system_score_gemma":0.0006290358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001787658,"about_ca_topic_score_gemma":0.0002072182,"domain_scores_codex":[0.990527,0.0004448971,0.002279497,0.002310215,0.00331615,0.001122294],"domain_scores_gemma":[0.9833436,0.0132676,0.0002645979,0.001377239,0.0004663947,0.001280566],"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":[0.01213946,0.0001816633,0.003343634,0.000006072074,0.00004097915,0.000009619909,0.00009661447,0.00005016408,0.00003640404,0.0003414846,0.1017494,0.8820046],"study_design_scores_gemma":[0.03050718,0.004026061,0.06235565,0.00008772863,0.00002490731,9.737151e-7,0.0006278384,0.02265526,0.00003130096,0.00499391,0.8742165,0.0004727188],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9487956,0.0003328751,0.01651036,0.02795034,0.002821521,0.001607041,0.00005340516,0.0001360249,0.001792829],"genre_scores_gemma":[0.9901689,0.0001259453,0.002543343,0.002692069,0.003261583,0.00006746576,0.000003908377,0.0000281943,0.001108572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8815318,"threshold_uncertainty_score":0.9998827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7814822954328613,"score_gpt":0.6425963769664341,"score_spread":0.1388859184664272,"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."}}