{"id":"W2950957248","doi":"10.1021/acsami.9b07522","title":"Design Molecular Topology for Wet–Dry Adhesion","year":2019,"lang":"en","type":"article","venue":"ACS Applied Materials & Interfaces","topic":"Surface Modification and Superhydrophobicity","field":"Materials Science","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Division of Materials Research; Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Adhesion; Topology (electrical circuits); Nanotechnology; Polymer science; Composite material; Chemical engineering; Mathematics","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":[0.0001574154,0.0004103681,0.0002029463,0.000374516,0.0002479311,0.0003646693,0.0004013884,0.0003608466,0.004403316],"category_scores_gemma":[0.0003103267,0.0002450113,0.0001767222,0.0002550319,0.0002359247,0.0007960686,0.0004186332,0.0006223346,0.001262878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002794879,"about_ca_system_score_gemma":0.0001530747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007218815,"about_ca_topic_score_gemma":0.0002154055,"domain_scores_codex":[0.9998928,0.00001694921,0.00001049694,0.00002856376,0.00003202091,0.00001906662],"domain_scores_gemma":[0.9998727,0.00002889073,0.00003652824,0.00001937218,0.00002070382,0.0000218097],"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":[0.00006351865,0.0001125961,0.000187495,0.0003459943,0.00002263858,0.0001351243,0.00004594157,0.00340316,0.9506624,0.02064111,0.001437887,0.02294216],"study_design_scores_gemma":[0.0001248441,0.000833407,0.0009714714,0.0000413145,0.00003689353,0.000312949,0.00007846456,0.02419996,0.9091805,0.00646115,0.05770183,0.00005714378],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7739251,0.003995196,0.158148,0.001158885,0.0007170634,0.0005564661,0.0007323113,0.001071483,0.05969536],"genre_scores_gemma":[0.9435757,0.002222884,0.04523574,0.0004310269,0.0000914632,0.0005367205,0.0004736203,0.0001502108,0.007282575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004403316,"threshold_uncertainty_score":0.01473057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0230263091195275,"score_gpt":0.2597439746315348,"score_spread":0.2367176655120073,"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."}}