{"id":"W3134137042","doi":"10.1016/j.bpj.2021.02.035","title":"Concentration sensing in crowded environments","year":2021,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Institute of General Medical Sciences; National Institutes of Health","keywords":"Computational biology; Computer science; Environmental science; Chemistry; Environmental chemistry; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.00003735448,0.0000469586,0.00006425543,0.00001170769,0.00002955765,0.00003469736,0.00004512631,0.00003171798,0.00003385027],"category_scores_gemma":[0.00000638633,0.00004929174,0.00003367462,0.00008406236,0.00001178311,0.0000482599,0.00001341408,0.000193678,0.00002505541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004527185,"about_ca_system_score_gemma":0.00000875943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.816126e-7,"about_ca_topic_score_gemma":0.000001077873,"domain_scores_codex":[0.9996101,0.00004439837,0.0001169976,0.00004413388,0.00008245528,0.0001019196],"domain_scores_gemma":[0.9998211,0.00001214025,0.00001401016,0.00009786835,0.00000665066,0.00004820103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000002020642,0.00002122329,0.00005983984,0.000001588372,0.000008771056,0.00006667904,0.00004694286,0.004591681,0.9850597,0.0001240163,0.0001513318,0.009866208],"study_design_scores_gemma":[0.00105975,0.00001748623,0.009830506,0.00007619078,0.00001286885,0.0001856035,0.00005670776,0.3404278,0.6309515,0.0002614711,0.0168527,0.0002673378],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9460163,0.000313993,0.05043046,0.000223042,0.0002798351,0.00003694894,5.910633e-7,0.00002888796,0.002669916],"genre_scores_gemma":[0.9983698,0.0002396237,0.001180909,0.00007284083,0.0000955811,2.383821e-7,0.00000428257,0.000007586896,0.00002909683],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3541082,"threshold_uncertainty_score":0.2010059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009369905492816712,"score_gpt":0.2096526656950576,"score_spread":0.2002827602022409,"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."}}