{"id":"W1997810092","doi":"10.1117/12.2080607","title":"Spinal cord deformation due to nozzle gas flow effects using optical coherence tomography","year":2015,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Toronto Metropolitan University","funders":"","keywords":"Optical coherence tomography; Context (archaeology); Nozzle; Materials science; Laser; Biomedical engineering; Deformation (meteorology); Computer science; Optics; Mechanical engineering; Composite material; Geology; Medicine; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006297725,0.0004614549,0.0005475234,0.0002587394,0.00009687051,0.0001853983,0.001075877,0.0002644163,0.000007461975],"category_scores_gemma":[0.0005228292,0.000424279,0.0005956744,0.001117893,0.0002506161,0.0007795251,0.0001797934,0.0004468031,0.000009762294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002744182,"about_ca_system_score_gemma":0.00004572137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001003523,"about_ca_topic_score_gemma":3.995823e-7,"domain_scores_codex":[0.9971557,3.3919e-8,0.0008279074,0.0004328134,0.0009456185,0.0006379865],"domain_scores_gemma":[0.9972736,0.0001411893,0.0001938929,0.0001185721,0.001810568,0.0004621661],"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":[0.0003737863,0.0002536136,0.0005237111,0.001409496,0.0006582988,6.234886e-7,0.0003426094,0.008513608,0.6510717,0.3287768,0.00371716,0.004358609],"study_design_scores_gemma":[0.00243456,0.002390767,0.003032991,0.001237125,0.0005551245,0.0001189631,0.0015953,0.619457,0.3580483,0.006923583,0.00263078,0.001575509],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921549,0.0001190188,0.002549663,0.0005900839,0.0003768208,0.001161188,0.00004494754,0.0003093234,0.00269405],"genre_scores_gemma":[0.6653237,0.00001447164,0.333815,0.00006974201,0.000309642,0.0003627436,0.000009709997,0.00008063302,0.00001441176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6109434,"threshold_uncertainty_score":0.9998209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01676248192339285,"score_gpt":0.2462026649743136,"score_spread":0.2294401830509207,"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."}}