{"id":"W3216579525","doi":"10.1109/eic49891.2021.9612318","title":"Application of Convolution Neural Network in Hydrophobicity Classification","year":2021,"lang":"en","type":"article","venue":"","topic":"High voltage insulation and dielectric phenomena","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Convolutional neural network; Silicone rubber; Computer science; Artificial intelligence; Deep learning; Artificial neural network; Convolution (computer science); Machine learning; Network topology; Materials science; Operating system","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":[0.0003926488,0.0004814356,0.0003412165,0.0008185948,0.0001908059,0.0004512304,0.0002897448,0.000534764,0.001017678],"category_scores_gemma":[0.0007480436,0.0001227622,0.0003250678,0.0006132924,0.0001855386,0.0004694716,0.0003008036,0.0002849298,0.0002689368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004308527,"about_ca_system_score_gemma":0.000325564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00462409,"about_ca_topic_score_gemma":0.003338854,"domain_scores_codex":[0.9998075,0.0000266898,0.00001461764,0.0000479346,0.00006526819,0.00003791042],"domain_scores_gemma":[0.9997599,0.00007035113,0.00002882173,0.00002060405,0.0001057347,0.00001463972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004723527,0.000310811,0.02349179,0.0001676025,0.00009798651,0.0003654977,0.0001088537,0.1858302,0.07364565,0.001874035,0.003939234,0.7096961],"study_design_scores_gemma":[0.000005161345,0.0000749758,0.007767703,0.000009839123,0.00001953149,0.00006808258,0.00002964764,0.9720736,0.01853174,0.0006861374,0.000722346,0.00001119908],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6567256,0.001755575,0.3303352,0.0004518656,0.0001588908,0.00008343918,0.0006025662,0.001846143,0.008040594],"genre_scores_gemma":[0.9632479,0.0003513488,0.03326235,0.00005201062,0.00002708583,0.00001776789,0.0003514857,0.00001737293,0.002672663],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00462409,"threshold_uncertainty_score":0.009194374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01738534822734825,"score_gpt":0.2492918925845618,"score_spread":0.2319065443572136,"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."}}