{"id":"W4416856554","doi":"10.1021/acsnanomed.5c00062","title":"Instructing a Chatbot to Design Nucleic Acid Probes for Diagnostics","year":2025,"lang":"en","type":"article","venue":"ACS Nano Medicine","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Barcode; Nucleic acid; Multiplex; Nucleic acid detection; Chatbot; Automation; Polymerase","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":[0.0005920606,0.0001475656,0.0003345015,0.0002763336,0.0001834847,0.0000105803,0.0001163618,0.0001148153,0.00005269197],"category_scores_gemma":[0.006897757,0.0001175838,0.00003692596,0.0005908516,0.00008439425,0.00005528498,0.00002921084,0.0001368712,0.00003666777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001315122,"about_ca_system_score_gemma":0.0003449886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002077469,"about_ca_topic_score_gemma":0.00003016221,"domain_scores_codex":[0.9986498,0.00003401344,0.0004982271,0.000289755,0.0001884014,0.0003397909],"domain_scores_gemma":[0.9982128,0.0008169896,0.00007798397,0.0002996121,0.0004038141,0.0001888721],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006862519,0.0002352936,0.01472509,0.0009566869,0.00009977265,0.00001246764,0.009543852,0.00002129234,0.09559206,0.005865439,0.0984709,0.7737909],"study_design_scores_gemma":[0.0007266845,0.0036568,0.003442845,0.004072479,0.0004191443,0.0000433114,0.009472232,0.0005782043,0.8818292,0.01238177,0.08303767,0.0003396634],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7746059,0.002467539,0.1032495,0.1097572,0.003654016,0.004299926,0.000004726429,0.0001999528,0.001761228],"genre_scores_gemma":[0.9767058,0.0003372293,0.01076118,0.009645625,0.001134242,0.0003325703,0.00002159037,0.00002350596,0.001038201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7862371,"threshold_uncertainty_score":0.8257758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1888332789002296,"score_gpt":0.4492369216087993,"score_spread":0.2604036427085696,"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."}}