{"id":"W2487978485","doi":"10.1109/icc.2016.7511444","title":"Receiver design for diffusion-based molecular communication: Gaussian mixture modeling","year":2016,"lang":"en","type":"article","venue":"","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Molecular communication; Gaussian; Bit error rate; Algorithm; Computer science; Interference (communication); Keying; Decoding methods; Transmitter; Telecommunications; Physics","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":[0.001059354,0.0006491084,0.0008204909,0.0004065099,0.0003731606,0.0008063383,0.001129035,0.001236481,0.0008029267],"category_scores_gemma":[0.002029836,0.0003901692,0.0004443463,0.0005539366,0.0006784439,0.001142877,0.0006117054,0.001056961,0.0004575686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009059354,"about_ca_system_score_gemma":0.0007743923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001817787,"about_ca_topic_score_gemma":0.001250347,"domain_scores_codex":[0.9993957,0.0001833058,0.00002580409,0.0001015523,0.0002447481,0.00004888432],"domain_scores_gemma":[0.9993101,0.0003759198,0.00007509359,0.00005417064,0.00016573,0.00001906889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001521078,0.00006739445,0.0007535152,0.0002101498,0.00007602262,0.0001213019,0.000184153,0.8130813,0.03699386,0.08163305,0.001006098,0.06572101],"study_design_scores_gemma":[0.000004857532,0.00002154732,0.00004467081,0.000004255669,0.000008495414,0.0000372058,0.000003688753,0.9929766,0.003328745,0.003053643,0.0005072742,0.000008944035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004067872,0.000242749,0.9949393,0.00009767892,0.00001280102,0.00001287578,0.000008547168,0.00009935491,0.0005189267],"genre_scores_gemma":[0.6041109,0.001528545,0.3895346,0.0002377825,0.00008202269,0.0001437961,0.00007887503,0.0000942448,0.004189289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001817787,"threshold_uncertainty_score":0.006573021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941582015195385,"score_gpt":0.2239882661353319,"score_spread":0.2045724459833781,"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."}}