{"id":"W4407911294","doi":"10.1186/s12859-025-06082-8","title":"Bacterial network for precise plant stress detection and enhanced crop resilience","year":2025,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Molecular Communication and Nanonetworks","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Key Technologies Research and Development Program","keywords":"Resilience (materials science); Crop; Biology; Computer science; DNA microarray; Stress (linguistics); Computational biology; Biotechnology; Genetics; Agronomy; Gene; Gene expression; Materials science","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":[0.0001460624,0.000268392,0.0002899424,0.0001751043,0.0002278835,0.0003958179,0.0002309738,0.0004912012,0.001820471],"category_scores_gemma":[0.000364467,0.0001568142,0.0001949599,0.000159859,0.0001815363,0.0005814845,0.0004247095,0.0003869226,0.0006832663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005034486,"about_ca_system_score_gemma":0.0003105667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000946773,"about_ca_topic_score_gemma":0.001561658,"domain_scores_codex":[0.9999089,0.0000203286,0.000003510162,0.00002587958,0.00002254929,0.00001882859],"domain_scores_gemma":[0.9999262,0.00002032275,0.00001797471,0.0000105025,0.00001255408,0.00001248038],"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":[0.0001558282,0.000118646,0.00222988,0.0003032032,0.00003815959,0.00008446205,0.00004726518,0.05356706,0.9045104,0.013054,0.001020319,0.02487076],"study_design_scores_gemma":[0.00003635462,0.0005422909,0.003368453,0.00004515254,0.00005269763,0.000209692,0.0001295444,0.5855804,0.3752368,0.008443348,0.02630919,0.00004599701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7178146,0.002750865,0.2661538,0.001124063,0.0002237964,0.0001330438,0.0006801914,0.00112906,0.00999057],"genre_scores_gemma":[0.9349582,0.001034466,0.06016253,0.0001052691,0.000009391772,0.0001088823,0.0003700612,0.00006087115,0.003190466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001820471,"threshold_uncertainty_score":0.006090105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008203899709209869,"score_gpt":0.2160120093574965,"score_spread":0.2078081096482866,"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."}}