{"id":"W4386070802","doi":"10.11159/icbes23.127","title":"In-Vivo Animal Trial of a Fiber-Optic Pressure Sensor Probe with Distributed Sensing Points for the Diagnosis of Lumbar Spinal Stenosis","year":2023,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"In vivo; Medicine; Stenosis; Optical fiber; Lumbar spinal stenosis; Fiber optic sensor; Lumbar; Pressure sensor; Biomedical engineering; Radiology; Biology; Computer science; Engineering; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001591137,0.0008188082,0.0006977757,0.000526164,0.0003215717,0.0003358862,0.000693818,0.001469495,0.0009709306],"category_scores_gemma":[0.0006329897,0.0004608742,0.0004409603,0.0002199794,0.0009893531,0.000675905,0.0003072851,0.001274102,0.0002008157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002827173,"about_ca_system_score_gemma":0.0003938982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003688726,"about_ca_topic_score_gemma":0.0005441559,"domain_scores_codex":[0.9993497,0.0001994764,0.00004180419,0.0001470549,0.0001287981,0.000133263],"domain_scores_gemma":[0.9992303,0.0002053283,0.0001803267,0.0001226694,0.00009524814,0.0001660621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.002707829,0.0028859,0.0005443216,0.0001305398,0.00004420897,0.0001157015,0.00008898881,0.000275662,0.9882609,0.00007717757,0.00009328679,0.004775411],"study_design_scores_gemma":[0.0009948523,0.1542877,0.004825546,0.00002719654,0.0002370387,0.0007304976,0.0001264602,0.003175059,0.8338668,0.0001070762,0.001585711,0.0000359354],"study_design_candidate":"nonrandomized_trial","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880468,0.0007177482,0.01007679,0.0002618339,0.0001537459,0.0002349581,0.0000919966,0.0001072417,0.0003089954],"genre_scores_gemma":[0.9747452,0.001151163,0.02079803,0.0002795506,0.0001360349,0.000565482,0.0003190724,0.00002856876,0.001976917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001591137,"threshold_uncertainty_score":0.008414805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01080788191998309,"score_gpt":0.2210190775973334,"score_spread":0.2102111956773503,"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."}}