{"id":"W2953549290","doi":"10.1109/access.2018.2889683","title":"An Experimentally Validated Channel Model for Molecular Communication Systems","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Research Foundation; National Research Foundation of Korea; Ministry of Education","keywords":"Molecular communication; Computer science; Channel (broadcasting); Focus (optics); Noise (video); Communications system; Function (biology); Sensitivity (control systems); Modulation (music); Experimental data; Data modeling; Electronic engineering; Acoustics; Telecommunications; Artificial intelligence; Physics; Optics; 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":[0.0003663822,0.0005599201,0.0004998451,0.0002955562,0.0004451713,0.0006094737,0.0009123716,0.001233544,0.002020431],"category_scores_gemma":[0.001396612,0.0001798967,0.000360326,0.0002045449,0.0006060893,0.001204925,0.0004671519,0.0008879923,0.0006839213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008104576,"about_ca_system_score_gemma":0.0008252312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003072002,"about_ca_topic_score_gemma":0.001618628,"domain_scores_codex":[0.9993591,0.0001198147,0.00002224815,0.0001512788,0.000259041,0.00008862818],"domain_scores_gemma":[0.9992441,0.0003535826,0.00007918386,0.00009121103,0.000207991,0.00002397728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001466118,0.0001731442,0.0007438239,0.0001513403,0.00002806373,0.0002126842,0.0001390523,0.8929767,0.07388697,0.0214711,0.001080836,0.008989612],"study_design_scores_gemma":[0.000005683873,0.00005150201,0.0001194595,0.000003224151,0.000004656732,0.00002267168,0.000008425026,0.9904438,0.008025895,0.0008221162,0.0004827156,0.000009836636],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1913719,0.000407183,0.7945282,0.0003247517,0.0001216165,0.0002445044,0.0005653017,0.001075153,0.01136133],"genre_scores_gemma":[0.9574391,0.0002786182,0.03649055,0.00009521811,0.0000245667,0.0002201422,0.0002186752,0.0000718096,0.00516148],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003072002,"threshold_uncertainty_score":0.006758988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03088093193745705,"score_gpt":0.3043406303976019,"score_spread":0.2734596984601448,"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."}}