{"id":"W2294456571","doi":"10.1109/jsac.2016.2525538","title":"Molecular MIMO: From Theory to Prototype","year":2016,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":221,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Ministry of Science ICT and Future Planning; National Research Foundation of Korea","keywords":"Molecular communication; Intersymbol interference; Computer science; MIMO; Transmitter; Channel (broadcasting); Channel state information; Interference (communication); Impulse response; Electronic engineering; Algorithm; Communications system; Detection theory; Telecommunications; Detector; Wireless; Mathematics","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":[0.0006088548,0.0004086901,0.0005738942,0.0004217524,0.0003022876,0.001413608,0.0007534759,0.0007792193,0.003417143],"category_scores_gemma":[0.001453707,0.0002724082,0.000408606,0.0005204612,0.0008047316,0.001011043,0.0006920673,0.001086137,0.001143877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000618788,"about_ca_system_score_gemma":0.0004440027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000654169,"about_ca_topic_score_gemma":0.000507428,"domain_scores_codex":[0.9996301,0.0001139476,0.00001243134,0.00004131641,0.0001608527,0.00004138507],"domain_scores_gemma":[0.9994127,0.0003109133,0.00004238471,0.00009013273,0.0001160894,0.00002783724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001205619,0.0001083169,0.0007775223,0.000476548,0.00005214726,0.0002515803,0.0001951631,0.3142959,0.01310089,0.566151,0.007314317,0.09715594],"study_design_scores_gemma":[0.00001988815,0.0001808965,0.0002072446,0.00007239334,0.00001733114,0.0002933253,0.00004417789,0.8888788,0.004753224,0.08830228,0.01719637,0.00003401704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01069868,0.004187704,0.944825,0.0006993712,0.0002940933,0.00007869824,0.0001345637,0.0004177161,0.03866415],"genre_scores_gemma":[0.6180847,0.009750175,0.3495527,0.0007703702,0.0007534956,0.0003754499,0.0003057237,0.000117566,0.02028991],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003417143,"threshold_uncertainty_score":0.01143146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01710389476387282,"score_gpt":0.2598129920274669,"score_spread":0.2427090972635941,"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."}}