{"id":"W4396982172","doi":"10.1109/tbme.2024.3401681","title":"Hybrid Hydrogel-Magnet Actuated Capsule for Automatic Gut Microbiome Sampling","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Gastrointestinal motility and disorders","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Capsule; Gut microbiome; Magnet; Microbiome; Sampling (signal processing); Biomedical engineering; Materials science; Computer science; Biology; Medicine; Engineering; Mechanical engineering; Bioinformatics; Detector; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001643853,0.0002327267,0.0002819497,0.0004281406,0.00007730978,0.00004076815,0.00008658563,0.00009553453,0.0002646375],"category_scores_gemma":[0.00005475239,0.0002150615,0.0002292854,0.0003817079,0.00007870376,0.00007832024,0.000001214779,0.0003692671,0.00009337409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001207155,"about_ca_system_score_gemma":0.000101399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001853818,"about_ca_topic_score_gemma":0.000001014941,"domain_scores_codex":[0.9986746,0.000006125097,0.0003393953,0.0003473259,0.0002214167,0.0004111711],"domain_scores_gemma":[0.9992471,0.0001956375,0.00001679692,0.0002005245,0.00003547625,0.000304437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001064718,0.0007798748,0.00000150824,0.00310177,0.000407766,0.0001589436,0.000257945,0.01357935,0.8843228,0.00005755023,0.001414038,0.09581204],"study_design_scores_gemma":[0.001647649,0.000944674,0.00008272988,0.001491894,0.0003272202,0.0008174086,0.00004760243,0.9487575,0.03467267,0.00008231617,0.01079303,0.0003352678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2020869,0.0001432444,0.7947907,0.0009486165,0.0007651042,0.0003827591,0.0001135657,0.000750458,0.00001866217],"genre_scores_gemma":[0.9817814,0.0000161208,0.01758331,0.0001373819,0.000100111,0.00008979644,0.00006026492,0.00005681896,0.0001748659],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9351782,"threshold_uncertainty_score":0.8769955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01630432339275049,"score_gpt":0.2581297648096417,"score_spread":0.2418254414168912,"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."}}