{"id":"W3120281654","doi":"10.3390/app11020662","title":"One-Step Liquid Phase Polymerization of HEMA by Atmospheric-Pressure Plasma Discharges for Ti Dental Implants","year":2021,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España; European Cooperation in Science and Technology","keywords":"Adhesion; Plasma polymerization; Coating; Biomaterial; Polymerization; Chemical engineering; Materials science; Acrylate; Protein adsorption; X-ray photoelectron spectroscopy; Titanium; Biocompatible material; Adsorption; Methacrylate; Monomer; Chemistry; Biomedical engineering; Polymer; Nanotechnology; Organic chemistry; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003093852,0.0001196688,0.000219509,0.0000114983,0.0003143412,0.00008803268,0.0003338442,0.00005987026,0.0005614901],"category_scores_gemma":[0.00004245796,0.0001094563,0.00004602462,0.0003175545,0.0003091742,0.0001851277,0.00006665414,0.00003424041,0.00003277978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001059994,"about_ca_system_score_gemma":0.0001089706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000367385,"about_ca_topic_score_gemma":0.00001666878,"domain_scores_codex":[0.9985794,0.00003584446,0.0002811176,0.0004418001,0.0003885031,0.000273334],"domain_scores_gemma":[0.9994202,0.0001066428,0.0001333543,0.000198671,0.00005796337,0.00008317447],"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":[0.00008919652,0.0001968829,0.0001488449,0.00002099065,0.000006019986,2.800991e-7,0.0002601268,0.00008721644,0.9962767,0.002027882,0.0003211951,0.0005647123],"study_design_scores_gemma":[0.0006162422,0.0001132873,0.0000465658,0.000008419242,0.00001626,0.000002905138,0.0008552497,0.003110932,0.9937736,0.0000532038,0.00126167,0.0001416083],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9902934,0.000257484,0.007478864,0.0001903723,0.0002433939,0.0002454112,0.0002715952,0.00004500647,0.0009744379],"genre_scores_gemma":[0.9932002,0.00001836852,0.00629838,0.0001106056,0.0000293034,0.00004694446,0.00005395908,0.00000875319,0.0002335012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003023715,"threshold_uncertainty_score":0.6147923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02455927346840565,"score_gpt":0.2823424806122991,"score_spread":0.2577832071438934,"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."}}