{"id":"W1824887011","doi":"10.24908/pceea.v0i0.4007","title":"DESIGNING ARTIFICIAL MUSCLES: A BIOMIMETIC APPROACH","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Université de Montréal; Centre Hospitalier Universitaire de Sherbrooke","funders":"","keywords":"Self-healing hydrogels; Artificial muscle; Isotonic; Vinyl alcohol; Materials science; Contraction (grammar); Divalent; Biophysics; Chemical engineering; Chemistry; Polymer chemistry; Actuator; Composite material; Computer science; Polymer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003932604,0.0003969318,0.0002430574,0.0003494839,0.0002997883,0.0005037726,0.0006180672,0.0005769947,0.001059907],"category_scores_gemma":[0.0002908502,0.0002679251,0.0002827877,0.0001491172,0.0007178447,0.0007169269,0.00045401,0.0006045783,0.000436344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002998018,"about_ca_system_score_gemma":0.0002775386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001283184,"about_ca_topic_score_gemma":0.0002922467,"domain_scores_codex":[0.999876,0.00003300163,0.00001253952,0.00002497719,0.00004006919,0.00001341566],"domain_scores_gemma":[0.9998677,0.00004763498,0.00002760126,0.00001983002,0.00001761192,0.00001957876],"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":[0.00001705327,0.00005518099,0.00009755747,0.0004295146,0.00001165399,0.00009790596,0.0001183254,0.003179428,0.9567704,0.01363203,0.0002410473,0.0253499],"study_design_scores_gemma":[0.000055157,0.000787118,0.0008623766,0.0001464638,0.00005085451,0.001510677,0.0001379525,0.01913217,0.8292455,0.01001868,0.1380053,0.00004773163],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2518776,0.02464784,0.6952388,0.002704396,0.0005352109,0.0004207341,0.0001606258,0.0005095794,0.0239053],"genre_scores_gemma":[0.4099432,0.02508845,0.5531223,0.0008085287,0.0001617829,0.0004276963,0.0001857741,0.00012382,0.01013848],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001059907,"threshold_uncertainty_score":0.003545761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764958157461385,"score_gpt":0.184996241655623,"score_spread":0.1673466600810092,"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."}}