{"id":"W3047151411","doi":"10.1177/1045389x20947167","title":"Tuning the hygro-mechanical response of paper-based systems using glycerol","year":2020,"lang":"en","type":"article","venue":"Journal of Intelligent Material Systems and Structures","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Cantilever; Flexibility (engineering); Stiffness; Frequency response; Materials science; Mechanical system; Work (physics); Microelectromechanical systems; Beam (structure); Resonance (particle physics); Mechanical engineering; Engineering; Structural engineering; Nanotechnology; Composite material; Electrical engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0004386786,0.0001800877,0.0004848018,0.00005675812,0.00006836144,0.0001492717,0.0001766592,0.00009440319,0.00002564587],"category_scores_gemma":[0.0001519624,0.000112391,0.00007517309,0.00007342335,0.00004523641,0.0001048818,0.0000248601,0.0001186014,4.313426e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003525287,"about_ca_system_score_gemma":0.00002470061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006776398,"about_ca_topic_score_gemma":5.157855e-7,"domain_scores_codex":[0.998417,0.0002277266,0.0008442125,0.00009660802,0.0002425803,0.0001719049],"domain_scores_gemma":[0.9991884,0.0001377093,0.0003338683,0.0001187428,0.0001023605,0.0001189014],"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":[0.0006089982,0.000001975514,0.00001189839,0.0002285238,0.00004463813,0.00001488612,0.0001518803,0.3437158,0.6547983,0.0003386531,0.00002912012,0.00005531442],"study_design_scores_gemma":[0.0007794299,0.0006757953,0.0002763117,0.0008151838,0.0001378414,0.0006740179,0.001607191,0.1073884,0.880942,0.0001758224,0.006095686,0.0004322735],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811292,0.0007433781,0.01520402,0.00003390308,0.002704232,0.0001136159,0.0000284483,0.00003038357,0.00001281195],"genre_scores_gemma":[0.9987429,0.00004342056,0.0004120209,0.00002673946,0.0007395827,0.00000127855,0.000001074244,0.00002995194,0.000003026824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2363275,"threshold_uncertainty_score":0.4583172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02995718037421039,"score_gpt":0.243235423199182,"score_spread":0.2132782428249717,"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."}}