{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001282194,0.0002233393,0.0001267362,0.0001347813,0.0001101457,0.0001417781,0.0001861922,0.0002195798,0.001410432],"category_scores_gemma":[0.0001754705,0.0001866809,0.0002201884,0.0001352229,0.0001330605,0.0001995616,0.000201274,0.000416648,0.0003247085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001484021,"about_ca_system_score_gemma":0.0001782079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002975985,"about_ca_topic_score_gemma":0.0006242667,"domain_scores_codex":[0.9999129,0.000008322744,0.000005790122,0.0000160868,0.00003709594,0.00001979579],"domain_scores_gemma":[0.9999424,0.00001626602,0.00002030677,0.000005483389,0.000009109141,0.000006454773],"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":[0.00001829406,0.000005604731,0.00003045451,0.00004364779,0.000001153293,0.00001562081,0.00001219525,0.00003011587,0.9979396,0.00002980401,0.00002029013,0.001853077],"study_design_scores_gemma":[0.000005412772,0.0001039402,0.001017576,0.000003168617,0.00000492564,0.00007471153,0.00000914619,0.0004437973,0.9971809,0.00001945559,0.00113383,0.000003148384],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853967,0.002243178,0.009872939,0.00009209869,0.00005284522,0.00004475033,0.00007404113,0.00009323472,0.002130189],"genre_scores_gemma":[0.9926913,0.0009405009,0.004525577,0.00002802349,0.00001629581,0.00002299157,0.0000561312,0.00002397808,0.001695234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001410432,"threshold_uncertainty_score":0.004718363,"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."}}