{"id":"W2909531635","doi":"10.1002/jbm.b.34307","title":"Synthetic fluorinated polyamides as efficient gene vectors","year":2019,"lang":"en","type":"article","venue":"Journal of Biomedical Materials Research Part B Applied Biomaterials","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hudbay Minerals (Canada)","funders":"Xinxiang Medical University; Foundation of Henan Educational Committee; National Natural Science Foundation of China","keywords":"Polyethylenimine; Polyamide; Transfection; Cationic polymerization; Cytotoxicity; Materials science; Polymer; HEK 293 cells; Gene delivery; Cell culture; Biophysics; Combinatorial chemistry; Gene; Polymer chemistry; Chemical engineering; Biology; Chemistry; Biochemistry; Genetics; In vitro; Composite material","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003894447,0.0002904876,0.0006502944,0.0004319428,0.0001180081,0.0002135919,0.00077189,0.0003912638,0.002153394],"category_scores_gemma":[0.00034806,0.00021487,0.0001472864,0.0003067403,0.000436053,0.000009132856,0.0004013748,0.0001120368,0.0009978856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006105338,"about_ca_system_score_gemma":0.0003293219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000318549,"about_ca_topic_score_gemma":5.132507e-7,"domain_scores_codex":[0.9959745,0.00047347,0.001162214,0.0004856551,0.001133292,0.0007708342],"domain_scores_gemma":[0.998113,0.00007768704,0.0004226165,0.000533913,0.0004608808,0.0003918651],"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":[0.00150868,0.0002503601,0.00001941451,0.00008929791,0.0001611915,0.00004659348,0.00003879354,0.000005585713,0.9939445,0.00008066526,0.003334159,0.0005207098],"study_design_scores_gemma":[0.0009389016,0.001706756,0.0002184141,0.0001245564,0.00001998823,0.0001907161,0.0001195004,0.000001757976,0.9750874,0.0001349239,0.02122181,0.0002352719],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961075,0.0002404624,0.0000227001,0.0002448501,0.00246985,0.0004738953,0.00009852288,0.00001493658,0.0003272456],"genre_scores_gemma":[0.9974878,0.0003325682,0.0001645252,0.00009466728,0.001481353,0.00003006804,0.000105248,0.00004518035,0.000258578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01885714,"threshold_uncertainty_score":0.9997799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02166261449521482,"score_gpt":0.3182887164846245,"score_spread":0.2966261019894096,"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."}}