{"id":"W4318954096","doi":"10.1109/tmbmc.2023.3240876","title":"Molecular Communication for Quorum Sensing Inspired Cooperative Drug Delivery","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Molecular Biological and Multi-Scale Communications","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Australian Research Council; University of Melbourne","keywords":"Quorum sensing; Drug delivery; Population; Diffusion; Absorption (acoustics); Drug; Molecular communication; Molecule; Chemistry; Biological system; Nanotechnology; Materials science; Chemical physics; Biophysics; Computer science; Pharmacology; Physics; Thermodynamics; Computer network; Biochemistry; Organic chemistry; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0001717591,0.0002237449,0.0002915738,0.0001579975,0.0002420267,0.0003030858,0.0003933237,0.0005528569,0.0009173506],"category_scores_gemma":[0.0003444684,0.0001226401,0.00017053,0.0001681247,0.0002604391,0.0004807234,0.000389156,0.0003372048,0.0002238932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004282064,"about_ca_system_score_gemma":0.0002235227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000280335,"about_ca_topic_score_gemma":0.0003415494,"domain_scores_codex":[0.9999021,0.00002212399,0.000004514815,0.00002237274,0.00003308263,0.00001567765],"domain_scores_gemma":[0.9998747,0.00005032655,0.00003376973,0.00001039451,0.00001700879,0.00001382939],"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":[0.0001013737,0.0001002992,0.0002814887,0.0003279963,0.000021701,0.0001914766,0.0000660219,0.03322178,0.9095684,0.02680035,0.0009994031,0.02831971],"study_design_scores_gemma":[0.00005364021,0.000638839,0.0005520132,0.00001707918,0.0000302541,0.0002031809,0.00002878932,0.7649834,0.2153988,0.004617361,0.01342961,0.00004697869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5125788,0.007466951,0.4638483,0.001414441,0.0005021782,0.0002129136,0.0001132828,0.000763186,0.01309988],"genre_scores_gemma":[0.9633579,0.0009513781,0.03354463,0.0001829651,0.00003558208,0.0001098474,0.00002853514,0.00001171366,0.001777563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009173506,"threshold_uncertainty_score":0.003106833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0393124705606219,"score_gpt":0.2680439714609928,"score_spread":0.2287315009003709,"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."}}