{"id":"W3206362056","doi":"10.1016/j.ijbiomac.2021.10.086","title":"Synthesis, characterization, and anti-tumor properties of O-benzoylselenoglycolic chitosan","year":2021,"lang":"en","type":"article","venue":"International Journal of Biological Macromolecules","topic":"Selenium in Biological Systems","field":"Nursing","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Key Research and Development Program of China; China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Chitosan; Chemistry; Apoptosis; In vitro; Nuclear chemistry; Selenium; Carbon-13 NMR; IC50; Fourier transform infrared spectroscopy; Active ingredient; Toxicity; Combinatorial chemistry; Stereochemistry; Biochemistry; Pharmacology; Organic chemistry; Chemical engineering; Medicine","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":[0.0001528218,0.0002681015,0.00008469385,0.0002767245,0.0001349193,0.0001511797,0.0001363066,0.0001965442,0.0007497347],"category_scores_gemma":[0.0002115299,0.00009869023,0.0002062197,0.0002476247,0.0001426199,0.0001453616,0.00008834419,0.0001946885,0.0001763537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002489786,"about_ca_system_score_gemma":0.0002848798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002805652,"about_ca_topic_score_gemma":0.003432082,"domain_scores_codex":[0.9999187,0.00000822158,0.000008377654,0.00001474281,0.00003199249,0.00001803228],"domain_scores_gemma":[0.9998533,0.00002036686,0.00004188209,0.00001196701,0.00005050904,0.00002203864],"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":[0.00004857303,0.00001021203,0.0001168781,0.00002387347,0.00000248837,0.00003423607,0.00001045464,0.00007062496,0.998374,0.00003618682,0.00001607286,0.001256426],"study_design_scores_gemma":[0.000003941611,0.0001492692,0.001524306,0.000001907148,0.000007653915,0.00004897051,0.00001179039,0.000340444,0.9973459,0.000005504561,0.0005561169,0.0000042416],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941263,0.0006689828,0.003542461,0.00006264818,0.00002006677,0.00004445439,0.0001377905,0.00003005557,0.001367197],"genre_scores_gemma":[0.9924731,0.0006079651,0.003563001,0.00004037028,0.00000661394,0.0000175726,0.0001833452,0.00001234889,0.003095685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002805652,"threshold_uncertainty_score":0.005578637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02585675939764142,"score_gpt":0.2561152893253354,"score_spread":0.230258529927694,"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."}}