{"id":"W1989868490","doi":"10.1109/glocom.2014.7037234","title":"Bounds on distance estimation via diffusive molecular communication","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Molecular communication; Cramér–Rao bound; Estimator; Upper and lower bounds; Maximum likelihood; Impulse (physics); Variance (accounting); Mathematics; Channel (broadcasting); Estimation theory; Statistics; Algorithm; Maximum likelihood sequence estimation; Computer science; Applied mathematics; Mathematical analysis; Physics; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001735986,0.0002963919,0.0002741388,0.0001016046,0.00008840959,0.0001126039,0.0007596478,0.000329357,0.00007216625],"category_scores_gemma":[0.00002630418,0.0003194146,0.0001227811,0.0001026502,0.00005175901,0.00003614672,0.0003481091,0.0007717108,0.0001314935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001478696,"about_ca_system_score_gemma":0.00001499019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001840036,"about_ca_topic_score_gemma":0.00002239744,"domain_scores_codex":[0.9988623,0.0001471137,0.0003424562,0.0002365777,0.0002232968,0.0001882584],"domain_scores_gemma":[0.9972876,0.00007943728,0.000106477,0.002381726,0.00006766088,0.00007704928],"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":[0.000008117798,0.00004490271,0.000008289278,0.0001321251,0.00007785753,0.000001568029,0.0001139865,0.9528942,0.0007380493,0.01926298,0.002966519,0.02375143],"study_design_scores_gemma":[0.0001766427,0.00001296549,0.000121975,0.0002025979,0.00002648834,0.000001312487,0.000003716397,0.9805058,0.001766957,0.007811853,0.009009151,0.0003605871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006175043,0.001451598,0.9373075,0.0002926697,0.0002397272,0.0003530125,0.000005400975,0.0005684227,0.05360664],"genre_scores_gemma":[0.9791381,0.0005936731,0.01882483,0.0003330682,0.00002525738,0.0001388386,0.0006901076,0.00007115459,0.0001849612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9729631,"threshold_uncertainty_score":0.9999258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006111982702647013,"score_gpt":0.2235370242520578,"score_spread":0.2174250415494108,"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."}}