{"id":"W2802613071","doi":"10.2196/medinform.9063","title":"A Neuroimaging Web Services Interface as a Cyber Physical System for Medical Imaging and Data Management in Brain Research: Design Study","year":2018,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; Florida Department of Health; University of Southern California; Biogen; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; National Science Foundation","keywords":"Neuroimaging; Computer science; Interface (matter); Human–computer interaction; Data science; World Wide Web; Medicine; Psychology; Neuroscience","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005315036,0.000212761,0.0003253849,0.000310184,0.0003537464,0.00019904,0.001291875,0.00006557218,0.00002200616],"category_scores_gemma":[0.008704442,0.0001743402,0.00002652421,0.0006133402,0.0006984415,0.0007999301,0.003022122,0.0006421767,0.00009975157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009958346,"about_ca_system_score_gemma":0.000170977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003498595,"about_ca_topic_score_gemma":0.00007200269,"domain_scores_codex":[0.9951969,0.0005317973,0.0005868655,0.0005182063,0.002577208,0.0005890094],"domain_scores_gemma":[0.9893071,0.009473011,0.0001090635,0.0006887159,0.0001197067,0.0003023716],"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":[0.00306711,0.008217966,0.008070265,0.01339064,0.0005573128,0.002576214,0.2781217,0.00004656341,0.002621719,0.02034657,0.280721,0.3822629],"study_design_scores_gemma":[0.002592235,0.000431247,0.0004527181,0.0006538368,0.00001705376,0.0001456979,0.04475703,0.9374852,0.0002888225,0.0004348737,0.01249823,0.0002430627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9604403,0.00004101394,0.007066708,0.02282187,0.0006181897,0.003981694,0.000030317,0.00027876,0.004721181],"genre_scores_gemma":[0.9934755,0.00001103696,0.0005481889,0.005289854,0.0002830575,0.0003093999,0.000003048806,0.00002350764,0.00005640588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9374386,"threshold_uncertainty_score":0.9996457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1221846674184832,"score_gpt":0.4244814521929944,"score_spread":0.3022967847745112,"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."}}