{"id":"W2171682620","doi":"10.1109/memsys.2011.5734596","title":"A confocal fiber optic catheter for in vivo thickness measurement of biological tissues","year":2011,"lang":"en","type":"article","venue":"","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; University of British Columbia","funders":"BC Cancer Agency; University of British Columbia","keywords":"Confocal; Microlens; Materials science; Biomedical engineering; Microelectromechanical systems; Optical fiber; Scanner; Optics; Cornea; Confocal microscopy; Biological tissue; Optoelectronics; Lens (geology); Medicine","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":[0.0001559437,0.00008017132,0.0001315047,0.00005158655,0.000008961233,0.000003795368,0.0001114323,0.00007443774,0.000790738],"category_scores_gemma":[0.0000193124,0.00006243782,0.0000509353,0.0001115918,0.00006088791,0.00003061191,0.00001244094,0.00005415333,0.00002304745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001642774,"about_ca_system_score_gemma":0.000006163452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003145209,"about_ca_topic_score_gemma":0.00003641475,"domain_scores_codex":[0.9994682,0.000008443781,0.0001849239,0.0001046942,0.00008331947,0.0001503889],"domain_scores_gemma":[0.9997017,0.0000415965,0.00001145733,0.0001429886,0.0000636424,0.00003862173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003541304,0.003524546,0.02163787,0.001264407,0.000664318,0.00001160208,0.008055507,0.001865316,0.3129045,0.6143829,0.003455414,0.03187946],"study_design_scores_gemma":[0.003086806,0.001713362,0.04141185,0.0002770604,0.0001411925,0.00001554704,0.0009066195,0.03216269,0.8715026,0.02947058,0.01755038,0.001761339],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8013912,0.000327607,0.06091212,0.00006463315,0.00009662207,0.001566925,0.00002943745,0.0003854927,0.1352259],"genre_scores_gemma":[0.974588,0.000004997111,0.02508891,0.000006996148,0.000007787459,0.0002547281,7.570008e-7,0.000008503315,0.00003937092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5849124,"threshold_uncertainty_score":0.8658026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08007550081291494,"score_gpt":0.260440628040136,"score_spread":0.180365127227221,"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."}}