{"id":"W2921509376","doi":"10.1016/j.matlet.2019.03.053","title":"Green preparation of copper surfaces with wettability contrast for guided fluid transport and fog harvesting application","year":2019,"lang":"en","type":"article","venue":"Materials Letters","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wetting; Materials science; Nanotechnology; Contact angle; Fabrication; Substrate (aquarium); Copper; Process engineering; Composite material; Metallurgy; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007493232,0.0001441715,0.0003135883,0.00003048475,0.00007069381,0.00004861974,0.0001197059,0.00005496751,0.0001506117],"category_scores_gemma":[0.00002046645,0.0001188704,0.00002499798,0.00005660105,0.000124355,0.000257359,0.00001229081,0.000020502,0.00001888821],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002573085,"about_ca_system_score_gemma":0.00002472371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009907909,"about_ca_topic_score_gemma":0.00006761966,"domain_scores_codex":[0.9987516,0.00008683727,0.000422941,0.0003796355,0.0001742717,0.000184671],"domain_scores_gemma":[0.9992898,0.00008908338,0.0001785874,0.0003004351,0.00009811823,0.00004398667],"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":[0.0002847814,0.00002431522,0.01487989,0.0001873497,0.000006489457,1.297011e-7,0.0003824937,0.0004673524,0.9836003,0.00007144173,0.0000657632,0.0000296907],"study_design_scores_gemma":[0.0007357001,0.00007828035,0.0346826,0.00002388548,0.00002052269,0.000002896355,0.00004735986,0.0004624102,0.9635091,0.00001905097,0.000266988,0.0001511767],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940789,0.0000111844,0.003425387,0.0007696488,0.0001404698,0.001297798,0.0001710043,0.00006238773,0.00004318276],"genre_scores_gemma":[0.9969636,0.000001516026,0.002480164,0.0002806927,0.00002707782,0.0001080468,0.00007554555,0.00001683555,0.00004649288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02009117,"threshold_uncertainty_score":0.4847393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01573983991477315,"score_gpt":0.2502125833057059,"score_spread":0.2344727433909327,"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."}}