{"id":"W3101875731","doi":"","title":"1Optimal Receiver Design for Diffusive Molecular Communication With Flow and Additive Noise","year":2016,"lang":"en","type":"article","venue":"","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":198,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Molecular communication; Detector; Computer science; Algorithm; Intersymbol interference; Noise (video); Transmitter; Interference (communication); Upper and lower bounds; Detection theory; Filter (signal processing); Bit error rate; Electronic engineering; Mathematics; Telecommunications; Decoding methods; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001697706,0.0008946238,0.0008060763,0.000486401,0.0004728679,0.001075231,0.001068799,0.001227989,0.00167308],"category_scores_gemma":[0.00305548,0.0004314047,0.000438399,0.0005219869,0.001063608,0.00158441,0.0009455379,0.0009000074,0.0005307285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001389119,"about_ca_system_score_gemma":0.001352039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001185939,"about_ca_topic_score_gemma":0.0009992208,"domain_scores_codex":[0.9987473,0.0004362677,0.00004821701,0.0002488703,0.000381669,0.0001375939],"domain_scores_gemma":[0.9985791,0.0007725466,0.0002036988,0.00009040719,0.0003061529,0.00004809225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004047317,0.0001484633,0.001515383,0.000280281,0.0001129556,0.0001898997,0.0001947378,0.7266933,0.05752425,0.1489349,0.001375625,0.06262552],"study_design_scores_gemma":[0.00001399159,0.00007677005,0.00007022324,0.00000833681,0.00001140873,0.00005473834,0.000007958113,0.9855666,0.006485119,0.007111033,0.0005812996,0.00001246538],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009772249,0.000112701,0.9888141,0.0001113365,0.00001599383,0.00001988047,0.00001990137,0.00008895257,0.001044936],"genre_scores_gemma":[0.7142654,0.0004277833,0.2799022,0.0002267395,0.00006991074,0.0001281891,0.00009688573,0.00004537891,0.004837521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001697706,"threshold_uncertainty_score":0.01007879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008505839802931028,"score_gpt":0.1932316032222736,"score_spread":0.1847257634193425,"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."}}