{"id":"W2842914447","doi":"10.1364/oe.26.018758","title":"Dual-beam manually actuated distortion-corrected imaging (DMDI): two dimensional scanning with a single-axis galvanometer","year":2018,"lang":"en","type":"article","venue":"Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Occupational Cancer Research Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Galvanometer; Distortion (music); Optics; Imaging phantom; Scanner; Perpendicular; Physics; Beam (structure); Sample (material); Stereo imaging; Computer science; Computer vision; Artificial intelligence; Mathematics; Laser; Bandwidth (computing)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007622379,0.0005306461,0.0004263643,0.0005656494,0.0001861596,0.0006954432,0.001340646,0.0006346969,0.0007403765],"category_scores_gemma":[0.001451425,0.0005422126,0.0002555602,0.0003098708,0.0008451049,0.0006331269,0.0008708602,0.0007498068,0.0002016232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005422509,"about_ca_system_score_gemma":0.0004601903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004741779,"about_ca_topic_score_gemma":0.0007744321,"domain_scores_codex":[0.9991575,0.0001512013,0.00003686008,0.0001719208,0.0003989771,0.00008349681],"domain_scores_gemma":[0.9989679,0.0003124992,0.0002859685,0.0001921166,0.0001636295,0.00007795602],"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":[0.0001868074,0.00002697578,0.0007790764,0.0001060979,0.00001123444,0.00007893676,0.00007537171,0.0009229589,0.9704724,0.0009107888,0.0002803017,0.02614896],"study_design_scores_gemma":[0.00002658517,0.0002059708,0.002296674,0.00000764603,0.00001144674,0.0006023301,0.00001882834,0.01973517,0.9732648,0.0001680099,0.003595181,0.00006746591],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4200037,0.001647629,0.5721703,0.0006465354,0.0002190485,0.0002214303,0.000255352,0.00125214,0.003583739],"genre_scores_gemma":[0.5578343,0.0004798389,0.438776,0.000176533,0.00005433273,0.0001313186,0.0001119756,0.0001000228,0.002335664],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001340646,"threshold_uncertainty_score":0.004031181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009893210072362565,"score_gpt":0.2246371900355187,"score_spread":0.2147439799631561,"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."}}