{"id":"W2062138732","doi":"10.1007/s11090-010-9261-4","title":"Anti-Fog Layer Deposition onto Polymer Materials: A Multi-Step Approach","year":2010,"lang":"en","type":"article","venue":"Plasma Chemistry and Plasma Processing","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Hôpital Saint-François d'Assise","funders":"Centre québécois sur les matériaux fonctionnels","keywords":"Materials science; Coating; Chemical engineering; Hexamethyldisiloxane; Spin coating; Polymer; Polycarbonate; Layer (electronics); Maleic anhydride; X-ray photoelectron spectroscopy; Silicon; Dissolution; Polymer chemistry; Fourier transform infrared spectroscopy; Composite material; Copolymer","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003465322,0.0002812445,0.0003010008,0.00002336719,0.0004564911,0.0004602218,0.0002312638,0.0002921364,0.0005933404],"category_scores_gemma":[0.00006886775,0.0002583768,0.0000381265,0.0001197025,0.0001882102,0.0004069953,0.00007252617,0.000274317,0.00006783592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002107563,"about_ca_system_score_gemma":0.00008269904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000877112,"about_ca_topic_score_gemma":0.0000140058,"domain_scores_codex":[0.9983767,0.00004222961,0.0003510394,0.000596161,0.0002493919,0.0003845082],"domain_scores_gemma":[0.9992554,0.00005191404,0.0001536462,0.0002661583,0.00008363494,0.0001892057],"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":[0.00005577556,0.0001421352,0.000511411,0.0003108931,0.000005077369,0.00000486009,0.0004308253,0.00001390445,0.9970734,0.00001092703,0.00003021101,0.001410622],"study_design_scores_gemma":[0.0006439557,0.00000631511,0.0002833769,0.00003947536,0.00002320869,0.0002048539,0.0002876256,0.02767738,0.9702231,0.000004068837,0.000275007,0.0003316176],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957657,0.0000993328,0.00119655,0.00008972728,0.0002441963,0.0001235738,0.00004979314,0.000180322,0.002250839],"genre_scores_gemma":[0.9818754,0.00001028167,0.01705324,0.00006342387,0.0001299114,0.00003504089,0.00006683997,0.00002860126,0.0007372217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02766347,"threshold_uncertainty_score":0.9999868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02318990369420596,"score_gpt":0.2478277111145228,"score_spread":0.2246378074203168,"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."}}