{"id":"W4283368232","doi":"10.2196/36914","title":"Mobile-Based and Self-Service Tool (iPed) to Collect, Manage, and Visualize Pedigree Data: Development Study","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"BRCA gene mutations in cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Computer science; JavaScript; Visualization; World Wide Web; Popularity; Data visualization; Interface (matter); Construct (python library); Service (business); Data collection; Software; User interface; Data science; Graphical user interface; Data mining; Psychology","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":[0.002341866,0.001271349,0.0004708581,0.001026158,0.0003194529,0.0008981383,0.002235132,0.0007113385,0.01382353],"category_scores_gemma":[0.00577173,0.000425748,0.0007346516,0.0004795486,0.0003414833,0.001774831,0.001810808,0.0007417062,0.004525037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004149972,"about_ca_system_score_gemma":0.00126456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001781045,"about_ca_topic_score_gemma":0.001138537,"domain_scores_codex":[0.9988769,0.0003892242,0.00008693019,0.0001828253,0.0003212758,0.0001428918],"domain_scores_gemma":[0.99664,0.001402936,0.0001149354,0.0002952955,0.001084514,0.0004623894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001876186,0.003824766,0.02548559,0.004144066,0.0001801283,0.003764016,0.003712415,0.00476371,0.04966708,0.0041057,0.07370049,0.8247759],"study_design_scores_gemma":[0.002336805,0.01440927,0.1009586,0.002624937,0.00107348,0.01237045,0.005310449,0.1207616,0.1400694,0.003760782,0.5954442,0.0008799048],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3419009,0.001378556,0.5563847,0.0009080262,0.0004662676,0.0139867,0.01136674,0.05448348,0.01912458],"genre_scores_gemma":[0.2036157,0.001049515,0.7508219,0.0004919152,0.00006215041,0.008936644,0.01385971,0.003026786,0.01813557],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01382353,"threshold_uncertainty_score":0.04624432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05858736029477004,"score_gpt":0.4210553007582096,"score_spread":0.3624679404634396,"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."}}