{"id":"W2283975603","doi":"10.1021/acs.langmuir.6b00006","title":"Liposome/Graphene Oxide Interaction Studied by Isothermal Titration Calorimetry","year":2016,"lang":"en","type":"article","venue":"Langmuir","topic":"Graphene and Nanomaterials Applications","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Liposome; Isothermal titration calorimetry; Adsorption; Chemistry; Differential scanning calorimetry; Graphene; Chemical engineering; Cationic liposome; Oxide; Materials science; Nanotechnology; Organic chemistry; Physical chemistry; Biochemistry; Thermodynamics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007012603,0.0006397878,0.0004684439,0.0004396358,0.0003700289,0.0004001636,0.0004306694,0.0004959766,0.001467193],"category_scores_gemma":[0.0007101995,0.0002028264,0.0003310696,0.0004654732,0.0004050267,0.0005113698,0.000286885,0.0009953148,0.0004858153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005275598,"about_ca_system_score_gemma":0.0002637304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001099927,"about_ca_topic_score_gemma":0.0009613064,"domain_scores_codex":[0.9994065,0.0001293333,0.00004048342,0.0001168645,0.0001941571,0.0001126764],"domain_scores_gemma":[0.9997009,0.000123472,0.00004725775,0.00002327181,0.00007973205,0.00002529322],"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":[0.00005266668,0.00002821328,0.0001149328,0.00004542694,0.000009116424,0.00001597131,0.00004896622,0.0001942769,0.9984864,0.000100642,0.00003359483,0.0008698282],"study_design_scores_gemma":[0.000005337886,0.00007766914,0.0004504755,0.000004159172,0.000009013927,0.000009849563,0.0000148606,0.002382857,0.9966007,0.00003531286,0.0004008892,0.000008963487],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804698,0.001617049,0.01392424,0.0001345642,0.00008128665,0.0001603384,0.0008939533,0.0002596892,0.002459151],"genre_scores_gemma":[0.9828856,0.001391271,0.01252397,0.0001116162,0.00003192603,0.0002738099,0.0007184448,0.00006100825,0.002002391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001467193,"threshold_uncertainty_score":0.004908264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006379710408529157,"score_gpt":0.2034400821427794,"score_spread":0.1970603717342503,"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."}}