{"id":"W2341777409","doi":"10.1109/isit.2016.7541454","title":"On the capacity of diffusion-based molecular timing channels","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Channel (broadcasting); Noise (video); Diffusion; Upper and lower bounds; Channel capacity; Molecular communication; Computer science; Statistical physics; Topology (electrical circuits); Algorithm; Physics; Electronic engineering; Telecommunications; Mathematics; Engineering; Mathematical analysis; Combinatorics; Transmitter","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":[0.002564777,0.001476441,0.001365609,0.002625943,0.001204393,0.0037015,0.0017338,0.001554343,0.007014326],"category_scores_gemma":[0.01821997,0.0006279204,0.0007097478,0.001839851,0.004782164,0.006171638,0.002982717,0.003649272,0.001084605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003536347,"about_ca_system_score_gemma":0.001525386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003121404,"about_ca_topic_score_gemma":0.001157179,"domain_scores_codex":[0.9977134,0.0006497109,0.00007608276,0.0002895739,0.0006844662,0.0005867114],"domain_scores_gemma":[0.9796116,0.01612844,0.0008890262,0.0009280716,0.001840762,0.0006020715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009957151,0.00003658702,0.0001844747,0.0001629949,0.00001789279,0.0001388303,0.0001733978,0.1008001,0.003145886,0.8863004,0.002664105,0.006275811],"study_design_scores_gemma":[0.00001708092,0.0000315631,0.0001665037,0.0001423475,0.00001641635,0.0001600766,0.00006694276,0.4134487,0.001770172,0.5804193,0.003704208,0.00005667721],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1539294,0.01588279,0.6610628,0.006895783,0.0006924704,0.000110028,0.001181025,0.000622607,0.1596231],"genre_scores_gemma":[0.9626167,0.00808525,0.0162811,0.00065952,0.000789702,0.0002730616,0.0003612367,0.0002385573,0.01069475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007014326,"threshold_uncertainty_score":0.02565807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02691371325963316,"score_gpt":0.2215761684629249,"score_spread":0.1946624552032917,"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."}}