{"id":"W2948245629","doi":"10.11159/iccste19.194","title":"Optical fibre bending sensor for vehicle weight detection","year":2019,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Civil, Structural and Transportation Engineering","topic":"Advanced Fiber Optic Sensors","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministerstvo Průmyslu a Obchodu; Ministerstvo Školství, Mládeže a Tělovýchovy","keywords":"Natural rubber; Materials science; Bending; Sensitivity (control systems); Composite material; Attenuation; Detector; Acoustics; Vibration; Optics; Electronic engineering; Engineering; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003340672,0.000135383,0.0001240193,0.00006907222,0.0000307361,0.00002903551,0.0001337485,0.00005466718,0.00002891983],"category_scores_gemma":[0.00001695277,0.0001113887,0.00005651543,0.00007452858,0.0000170335,0.000221932,0.000005132315,0.0001277405,0.000001252708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003562879,"about_ca_system_score_gemma":0.0000035114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001745149,"about_ca_topic_score_gemma":0.000004121015,"domain_scores_codex":[0.9993376,4.374642e-7,0.00019861,0.0001525033,0.0001794886,0.00013137],"domain_scores_gemma":[0.9997135,0.00003745413,0.00004904571,0.00003943076,0.0001252879,0.00003529814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006060268,0.000003520126,0.002986849,0.000262512,0.00008014945,2.088599e-7,0.0003258996,0.05423211,0.8735142,0.06635315,0.00000560635,0.002175182],"study_design_scores_gemma":[0.0006156738,0.00005925422,0.0499619,0.0001866465,0.00002685237,0.00000709659,0.0001942733,0.5673168,0.379402,0.00178879,0.0001936427,0.0002470857],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967363,0.0000110713,0.001463483,0.0001274052,0.0006172763,0.0002220184,0.00003248793,0.00009110357,0.0006988096],"genre_scores_gemma":[0.9978712,0.00001286548,0.00194044,0.0000086074,0.00006203081,0.00001416411,0.00000743111,0.00002167585,0.00006162694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5130847,"threshold_uncertainty_score":0.4542299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009604276100550032,"score_gpt":0.21078181078028,"score_spread":0.20117753467973,"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."}}