{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002020674,0.001793087,0.0006410962,0.0005080822,0.000431257,0.001007619,0.001771792,0.001342907,0.01045025],"category_scores_gemma":[0.006376648,0.0009528548,0.000650517,0.0001727016,0.0007877005,0.001338059,0.001322009,0.001344426,0.005566804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006654591,"about_ca_system_score_gemma":0.001182654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008893344,"about_ca_topic_score_gemma":0.001301699,"domain_scores_codex":[0.9990596,0.000328354,0.00006305076,0.000301245,0.0001495766,0.00009824398],"domain_scores_gemma":[0.9950495,0.003511408,0.0002824679,0.000539488,0.0003978865,0.0002192348],"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":[0.002092356,0.001460536,0.01088683,0.002190037,0.0001594689,0.00200458,0.00501792,0.04513885,0.4560805,0.02048654,0.03640842,0.418074],"study_design_scores_gemma":[0.0002342511,0.0007849789,0.00210178,0.0002121595,0.0001109717,0.0007160874,0.000515833,0.634461,0.2560677,0.01247245,0.09214799,0.0001746918],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03018749,0.0001327341,0.9062203,0.0004639546,0.0001473615,0.0005780071,0.000540699,0.05656508,0.005164424],"genre_scores_gemma":[0.2859005,0.0001845494,0.6946897,0.0009728686,0.00005782249,0.001368686,0.001020792,0.00298967,0.01281546],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01045025,"threshold_uncertainty_score":0.03495955,"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."}}