{"id":"W4409665917","doi":"10.1038/s41467-025-58996-9","title":"Engineering coupled consortia-based biosensors for diagnostic","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"Technion-Israel Institute of Technology; European Commission; Canadian Institute for Advanced Research","keywords":"Biosensor; Computer science; Computational biology; Nanotechnology; Biology; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001380454,0.0001031842,0.0001139777,0.00008210964,0.0001428368,0.00001637775,0.0005309118,0.0002518765,0.000003829334],"category_scores_gemma":[0.0009591861,0.0001103841,0.0001278515,0.0002411288,0.00006246584,0.000001193572,0.0001201162,0.0001741018,0.000002707953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001798496,"about_ca_system_score_gemma":0.00009239256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002303846,"about_ca_topic_score_gemma":0.0001003924,"domain_scores_codex":[0.9994387,0.00003712549,0.0001555289,0.0001802755,0.00004900614,0.0001393505],"domain_scores_gemma":[0.9980103,0.0003514824,0.00004771497,0.001391202,0.0001632063,0.00003605622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000105354,0.0005571551,0.03726236,0.0001529155,0.001425413,0.000001172079,0.00003144221,0.06615812,0.7723839,0.0265023,0.09273874,0.002681126],"study_design_scores_gemma":[0.001058389,0.00005254076,0.01324396,0.00005838287,0.0003469372,0.000001479137,0.00002643659,0.1496677,0.07887509,0.000110935,0.7561799,0.0003781494],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6916497,0.1194157,0.1561057,0.02580655,0.001165415,0.002825469,0.0002269867,0.0003090682,0.002495395],"genre_scores_gemma":[0.9875177,0.0002700681,0.01075695,0.0005504288,0.00004276547,0.0001349744,0.0004491725,0.00001402909,0.0002639845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6935088,"threshold_uncertainty_score":0.4501331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007346231875330661,"score_gpt":0.2715238895781313,"score_spread":0.2641776577028006,"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."}}