{"id":"W4378895148","doi":"10.1016/j.porgcoat.2023.107680","title":"A melting pre-bonding method for fabrication of mechanical-robust superhydrophobic powder coatings","year":2023,"lang":"en","type":"article","venue":"Progress in Organic Coatings","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Materials science; Coating; Durability; Composite material; Abrasion (mechanical); Superhydrophobic coating; Corrosion; Powder coating; Contact angle; Fabrication; Polyester; Curing (chemistry)","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":[0.003002418,0.0002576646,0.0004994893,0.0002824957,0.0002729088,0.00009470859,0.0005190543,0.0001711507,0.0006168958],"category_scores_gemma":[0.001692899,0.0002564464,0.0001105857,0.001429983,0.0001605181,0.0002406728,0.000254847,0.0001887855,0.00006992735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001686009,"about_ca_system_score_gemma":0.0001178396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001553938,"about_ca_topic_score_gemma":0.00002762442,"domain_scores_codex":[0.9970531,0.0002296708,0.0009414657,0.0007087371,0.0004777474,0.0005892252],"domain_scores_gemma":[0.9978164,0.0008582292,0.0004252198,0.0004668738,0.000332224,0.000101033],"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":[0.00004564921,0.00009149709,0.00568003,0.0001840305,0.000005157,0.00000160504,0.004046921,0.0001152727,0.985369,0.001512165,0.000152216,0.002796483],"study_design_scores_gemma":[0.00095047,0.0001207453,0.002047325,0.0001454711,0.00002949218,0.00000665622,0.001360366,0.05762652,0.9357857,0.001281508,0.0002960924,0.0003497237],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704795,0.0001305568,0.02683845,0.0007327031,0.0003108119,0.001006069,0.00002485712,0.0003927366,0.0000842513],"genre_scores_gemma":[0.9341955,0.00001024019,0.06498793,0.00008262906,0.00005900941,0.00028507,0.00003351809,0.00006662621,0.0002795275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05751125,"threshold_uncertainty_score":0.9999888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0390800030503582,"score_gpt":0.3204616956615571,"score_spread":0.2813816926111989,"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."}}