{"id":"W2043797940","doi":"10.1063/1.4893010","title":"Mechanochromic polyurethane strain sensor","year":2014,"lang":"en","type":"article","venue":"Applied Physics Letters","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Materials science; Thermoplastic polyurethane; Elastomer; Composite material; Polyurethane; Softening; Deformation (meteorology); Strain (injury); Stress relaxation; Stress (linguistics); Polymer; Thermoplastic elastomer; Relaxation (psychology); Copolymer","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":[0.00008040877,0.0002020092,0.0001882667,0.00002410761,0.0001324835,0.00004821274,0.0002127825,0.00003253625,0.0001607085],"category_scores_gemma":[3.68333e-7,0.0002083804,0.00009773287,0.0001453163,0.00007472583,0.00004372583,0.00004726854,0.0001799796,0.0002092435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001797713,"about_ca_system_score_gemma":0.00001096645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006825209,"about_ca_topic_score_gemma":3.053182e-7,"domain_scores_codex":[0.9990709,0.00001426123,0.0001660869,0.0003137667,0.0001159322,0.0003190681],"domain_scores_gemma":[0.9993705,0.00003341177,0.00009354145,0.0004153033,0.00001385596,0.00007338113],"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":[0.000002275633,0.00002761059,0.00005122642,0.000003156537,0.00001601702,5.123887e-8,0.00004432479,0.00008189548,0.6785061,0.3112758,0.002114721,0.007876754],"study_design_scores_gemma":[0.000610986,0.00002295127,0.0001515854,0.00001353092,0.00004793056,5.866416e-7,0.00009313506,0.0004164028,0.9424357,0.03554769,0.02006805,0.0005913874],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3808653,0.000001578776,0.5984084,0.0007970849,0.00005057402,0.0003306976,0.0000847569,0.0001778162,0.01928378],"genre_scores_gemma":[0.9864834,2.620385e-7,0.01056985,0.001885538,0.0006389752,0.0001162654,0.0001707181,0.00004328077,0.00009172281],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6056181,"threshold_uncertainty_score":0.8497508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006436348534395312,"score_gpt":0.2292639793268103,"score_spread":0.222827630792415,"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."}}