{"id":"W4393869591","doi":"10.1017/cts.2024.339","title":"388 Prototyping a mobile phone application for Chimeric Antigen Receptor (CAR) T-cell therapy patient monitoring and data collection post-discharge","year":2024,"lang":"en","type":"article","venue":"Journal of Clinical and Translational Science","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Chimeric antigen receptor; Mobile phone; Rapid prototyping; Phone; Computer science; Medicine; Engineering; Telecommunications; Immunology; Immunotherapy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002895796,0.0006342899,0.0003234596,0.0006905072,0.0003470482,0.0009923469,0.001015509,0.0008129633,0.01210592],"category_scores_gemma":[0.007548159,0.0002526095,0.0007260733,0.0002250244,0.0001884446,0.001063871,0.0006657157,0.0004419279,0.00392445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002540011,"about_ca_system_score_gemma":0.0007714034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005073669,"about_ca_topic_score_gemma":0.0009800988,"domain_scores_codex":[0.9984463,0.0007902182,0.0001595412,0.0001481704,0.0003765998,0.00007925628],"domain_scores_gemma":[0.993911,0.004271297,0.0002080211,0.0002451662,0.001194681,0.0001698353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001132784,0.0009560589,0.008511433,0.005861393,0.0001243235,0.00236413,0.004667705,0.001204937,0.05002948,0.001722586,0.05102235,0.8724028],"study_design_scores_gemma":[0.001635966,0.01389618,0.0848439,0.007898134,0.001097186,0.01078564,0.00945401,0.03067078,0.1062908,0.00582798,0.726819,0.0007804537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3401366,0.004109951,0.5327094,0.00571284,0.001401964,0.01911148,0.005897584,0.02032551,0.07059462],"genre_scores_gemma":[0.3329608,0.002710616,0.6226904,0.002208127,0.0002204474,0.01177304,0.002696921,0.0005880798,0.0241514],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01210592,"threshold_uncertainty_score":0.04049832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1259746076426856,"score_gpt":0.511752478268884,"score_spread":0.3857778706261984,"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."}}