{"id":"W3010105331","doi":"10.1109/access.2020.3005603","title":"Novel Molecular Signaling Method and System for Molecular Communication in Human Body","year":2020,"lang":"en","type":"preprint","venue":"IEEE Access","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Alfaisal University","keywords":"Molecular communication; ADME; Nanorobotics; Transmitter; Computer science; Human body; Channel (broadcasting); Computational biology; Artificial intelligence; Bioinformatics; Pharmacokinetics; Biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000212028,0.0003287732,0.0002363306,0.0002951265,0.0002781723,0.0004403512,0.0004734863,0.0006695145,0.002341189],"category_scores_gemma":[0.0002730666,0.0001390035,0.0002448255,0.0001819912,0.0003579178,0.0006352917,0.0004536519,0.0004763539,0.0009482657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003753174,"about_ca_system_score_gemma":0.0003415921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002950421,"about_ca_topic_score_gemma":0.0003961361,"domain_scores_codex":[0.999769,0.00003294392,0.00001104152,0.00006226673,0.0001021143,0.00002251651],"domain_scores_gemma":[0.9998901,0.00002515846,0.00002945365,0.00001553329,0.00002909937,0.00001073689],"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":[0.0001293555,0.00006343512,0.0003276557,0.0003688985,0.0000208667,0.0001466786,0.00009467142,0.002110719,0.915292,0.0339736,0.00241244,0.04505964],"study_design_scores_gemma":[0.00005387562,0.0009896623,0.001080097,0.00009214251,0.00007864781,0.00126675,0.00007949486,0.0819204,0.7801056,0.004704315,0.1295314,0.00009762391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1262177,0.007598572,0.8219191,0.001412554,0.001051873,0.0003794134,0.0004148206,0.001587553,0.03941843],"genre_scores_gemma":[0.6954013,0.004100325,0.2759849,0.000836613,0.0002614881,0.0004917549,0.0002293515,0.00008934136,0.022605],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002341189,"threshold_uncertainty_score":0.00783205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04685520202201469,"score_gpt":0.3394848859307434,"score_spread":0.2926296839087287,"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."}}