{"id":"W2803925604","doi":"10.1016/j.ab.2018.05.023","title":"Investigation of binding characteristics of immobilized toll-like receptor 3 with poly(I:C) for potential biosensor application","year":2018,"lang":"en","type":"article","venue":"Analytical Biochemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Royal Military College of Canada","funders":"Defence Research and Development Canada","keywords":"TLR3; Biosensor; Dissociation constant; Surface plasmon resonance; Chemistry; Toll-like receptor; Analyte; Combinatorial chemistry; Receptor; Nucleic acid; Aptamer; Biophysics; Innate immune system; Nanotechnology; Molecular biology; Biochemistry; Materials science; Chromatography; Biology; Nanoparticle","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":[0.0001477483,0.0001606915,0.0002671402,0.00005061975,0.00005212205,0.000009456468,0.0001320032,0.0002148113,0.000003361312],"category_scores_gemma":[0.00008374325,0.0001342785,0.0001300001,0.0002009183,0.0005385117,0.000003648305,0.0000444273,0.00005190112,0.000001048235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000152437,"about_ca_system_score_gemma":0.00006923904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006169088,"about_ca_topic_score_gemma":0.000001086666,"domain_scores_codex":[0.9989049,0.00001676157,0.0003813696,0.0003739097,0.0001456743,0.0001773601],"domain_scores_gemma":[0.99878,0.00001781669,0.0003076058,0.0003784878,0.0004393953,0.00007674676],"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":[0.0003607586,0.0000380042,0.001074997,0.00007517333,0.000097834,2.262566e-7,0.000005450856,1.095256e-7,0.9969642,0.00002725812,0.0002404261,0.001115555],"study_design_scores_gemma":[0.0003392829,0.0004178781,0.0001614185,0.00004314972,0.0001249114,0.000006757919,0.00003816607,0.0003453277,0.9976815,0.00002249589,0.0006508198,0.0001682984],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.984794,0.00003598732,0.01463387,0.00009716796,0.00002309772,0.0001704936,0.0001525249,0.00001867244,0.00007420085],"genre_scores_gemma":[0.9834843,0.00003185651,0.01519552,0.00005173142,0.000220708,0.00001157428,0.0007356717,0.00001790799,0.0002507513],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001309703,"threshold_uncertainty_score":0.5475718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008392592175247944,"score_gpt":0.2584755989900376,"score_spread":0.2500830068147896,"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."}}