{"id":"W2606579376","doi":"10.1126/sciadv.1602200","title":"Bend, stretch, and touch: Locating a finger on an actively deformed transparent sensor array","year":2017,"lang":"en","type":"article","venue":"Science Advances","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":359,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Capacitive sensing; Materials science; Wearable computer; Tactile sensor; Bending; Wearable technology; Optoelectronics; Capacitance; Computer science; Fabrication; Touchpad; Electrical conductor; Bent molecular geometry; Pressure sensor; Acoustics; Electrode; Nanotechnology; Computer hardware; Artificial intelligence; Embedded system; Mechanical engineering; Robot; Physics; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001583851,0.0001641676,0.0001663603,0.00006594841,0.0007239867,0.0002410094,0.0003326596,0.0000293333,0.0000119194],"category_scores_gemma":[0.0001752992,0.0001372433,0.00001712179,0.00007620296,0.0004526741,0.001810156,0.00001766346,0.00008332114,0.000005766615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004269367,"about_ca_system_score_gemma":0.00001881663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001983382,"about_ca_topic_score_gemma":0.00007494388,"domain_scores_codex":[0.998904,0.00001010247,0.0001489337,0.0003308546,0.0002254827,0.0003805548],"domain_scores_gemma":[0.9993568,0.0000436723,0.00007068443,0.000347637,0.00003822658,0.0001429549],"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":[0.00001805459,0.00001535081,0.000760748,0.00004458869,0.000004376873,0.000005129825,0.0007450008,0.08285734,0.7877732,0.0001900271,0.000001070463,0.1275851],"study_design_scores_gemma":[0.0002658843,0.0001329635,0.01523938,0.0001294416,0.000007244555,0.000009496141,0.000696755,0.002970249,0.9783655,0.0008668864,0.0009531265,0.0003630707],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946169,0.00007034128,0.001628776,0.00004050371,0.0004855104,0.00007092887,0.00001134858,0.0001510448,0.002924594],"genre_scores_gemma":[0.9930691,0.00006276773,0.006674849,0.00002394834,0.0001011106,0.00001028874,0.000001480716,0.00001675881,0.00003968032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1905923,"threshold_uncertainty_score":0.5596622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03595689475179489,"score_gpt":0.2966712126647604,"score_spread":0.2607143179129656,"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."}}