{"id":"W2750060874","doi":"10.1021/acsami.7b07519","title":"Optimization and Changes in the Mode of Proteolytic Turnover of Quantum Dot–Peptide Substrate Conjugates through Moderation of Interfacial Adsorption","year":2017,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Quantum Dots Synthesis And Properties","field":"Materials Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canada Research Chairs; Michael Smith Health Research BC; Canada Foundation for Innovation","keywords":"Materials science; Adsorption; Moderation; Quantum dot; Substrate (aquarium); Chemical engineering; Peptide; Chemical physics; Nanotechnology; Organic chemistry; Chemistry; Biochemistry","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":[0.0006299733,0.0001874434,0.0004679998,0.0000543921,0.00009608237,0.0001851635,0.0004151363,0.0001015107,0.000128411],"category_scores_gemma":[0.0000784299,0.0001246196,0.00001281577,0.0000317765,0.0004363601,0.0004020853,0.0001216417,0.00005195965,0.000003380425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001146438,"about_ca_system_score_gemma":0.00002399967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000906024,"about_ca_topic_score_gemma":0.0001883431,"domain_scores_codex":[0.9986124,0.0001214787,0.0006170466,0.0002527246,0.0002227782,0.0001735529],"domain_scores_gemma":[0.9985529,0.00007584746,0.0008766421,0.000388942,0.00009368816,0.00001197968],"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":[0.0005130498,0.00006081492,0.00005518038,0.0002989722,0.00001166169,1.825844e-7,0.004645126,0.002767695,0.9861881,0.005368468,0.000007226631,0.00008352449],"study_design_scores_gemma":[0.0003378101,0.0001676248,0.0002979545,0.0002407491,0.00002763665,0.000001653301,0.0008032454,0.0006477984,0.9947021,0.002643717,0.000001818463,0.0001279047],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983099,0.0001064456,0.0003394397,0.0001755986,0.0001649266,0.0006043349,0.00009526534,0.00001198467,0.0001920687],"genre_scores_gemma":[0.9991487,0.0002079596,0.0004786138,0.00001537011,0.00003546453,0.00008390217,0.000007452822,0.00001559456,0.000006943511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008513989,"threshold_uncertainty_score":0.508184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03062073517602623,"score_gpt":0.2693432053029515,"score_spread":0.2387224701269252,"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."}}