{"id":"W2158035912","doi":"10.1021/bm900097s","title":"New Insights into Chitosan−DNA Interactions Using Isothermal Titration Microcalorimetry","year":2009,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":157,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Chitosan; Isothermal microcalorimetry; Isothermal titration calorimetry; Chemistry; Enthalpy; Titration; Protonation; Binding constant; Stoichiometry; Analytical Chemistry (journal); Physical chemistry; Chromatography; Binding site; Organic chemistry; Thermodynamics; Ion; Biochemistry","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":[0.00002198333,0.0001780805,0.0001149586,0.00009136376,0.0001140522,0.00005926376,0.0001843595,0.0001215664,0.00003429846],"category_scores_gemma":[0.00001437198,0.000171979,0.0001105973,0.000129732,0.00003203324,0.00001372092,0.0000419936,0.00006421725,0.00004608294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001365701,"about_ca_system_score_gemma":0.00008832953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000140431,"about_ca_topic_score_gemma":0.00007435484,"domain_scores_codex":[0.9991547,0.00003366442,0.0002019716,0.0003254413,0.00009363843,0.0001906129],"domain_scores_gemma":[0.9995268,0.000003410388,0.00007008087,0.000261683,0.00003881169,0.00009921911],"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":[0.00005454025,0.00004959538,0.0000785616,0.000003013047,0.00003603811,0.000007116486,0.0001227433,0.000009044949,0.9843702,0.00005791152,0.001244688,0.01396659],"study_design_scores_gemma":[0.000250826,0.0002579179,0.001867912,0.00002089855,0.00001937017,0.00003723217,0.00004946992,0.0001074986,0.991623,0.0002736084,0.005272504,0.0002197665],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.967831,0.001115702,0.02881035,0.0001177254,0.0002745054,0.00009277389,0.000003194892,0.00002406647,0.001730749],"genre_scores_gemma":[0.9933138,0.00006169038,0.005278002,0.0005378704,0.0005146025,0.000001759693,0.00008956299,0.00001615986,0.0001865817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02548284,"threshold_uncertainty_score":0.7013099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117543634256424,"score_gpt":0.2725976966386699,"score_spread":0.2608433332130275,"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."}}