{"id":"W4379260569","doi":"10.1002/app.54262","title":"Step by step progress to achieve an icephobic silicone‐epoxy hybrid coating: Tailoring matrix composition and additives","year":2023,"lang":"en","type":"article","venue":"Journal of Applied Polymer Science","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Sciences and Engineering Research Council of Canada; Cégep de Chicoutimi","funders":"Institut Nordique De Recherche En Environnement Et En Santé Au Travail; Mitacs","keywords":"Materials science; Composite material; Epoxy; Silicone; Coating; Curing (chemistry); Ultimate tensile strength; Silane; Adhesion; Fourier transform infrared spectroscopy; Silicone resin; Wetting; Sessile drop technique; Chemical engineering","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":[0.0002490871,0.000749973,0.0002578198,0.0003021167,0.0001448824,0.0002320912,0.0002990898,0.0002784743,0.0009961596],"category_scores_gemma":[0.0003279283,0.00022201,0.0002930254,0.0001988205,0.0001280615,0.0002706938,0.0002639105,0.0006081134,0.0005266944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001552375,"about_ca_system_score_gemma":0.0002491807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004335389,"about_ca_topic_score_gemma":0.001631292,"domain_scores_codex":[0.9998397,0.00001467947,0.00001602603,0.00003485832,0.00006588034,0.00002887688],"domain_scores_gemma":[0.9998198,0.00003201386,0.00005266112,0.00002168357,0.00005424579,0.00001958077],"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":[0.00001319999,0.00002129875,0.0000519233,0.00006647573,0.00000804758,0.00003863027,0.00001887287,0.0001194609,0.9978791,0.00004442959,0.00004262231,0.001695944],"study_design_scores_gemma":[0.000003047617,0.0001361895,0.0004945297,0.000005069816,0.00001093544,0.00005474603,0.00001056132,0.0005210149,0.9973319,0.00001378307,0.001412581,0.000005611042],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9577111,0.002162432,0.03407485,0.0001544585,0.0001170417,0.0002808508,0.0003452226,0.0003614737,0.004792518],"genre_scores_gemma":[0.9318265,0.002629754,0.06112242,0.0001019659,0.00002330852,0.0001362498,0.0003142871,0.0001178267,0.003727656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009961596,"threshold_uncertainty_score":0.003332555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01564479337142564,"score_gpt":0.281878579892213,"score_spread":0.2662337865207874,"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."}}