{"id":"W2589680139","doi":"10.1117/12.2254926","title":"Optimization of data processing with the Akinetic swept-laser: algorithm to automatically adjust the A-scan synchronization delay","year":2017,"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":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Synchronization (alternating current); Computer science; Algorithm; Telecommunications","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":[],"consensus_categories":[],"category_scores_codex":[0.0006893942,0.00034556,0.0003737632,0.00008865065,0.0003272821,0.0003451309,0.003171321,0.0001519099,0.00001361914],"category_scores_gemma":[0.0004256424,0.0002185675,0.0002168101,0.0005217415,0.0005530599,0.0009454916,0.0003763752,0.0003472677,0.000001631591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001053192,"about_ca_system_score_gemma":0.00005579339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001291197,"about_ca_topic_score_gemma":0.000001564837,"domain_scores_codex":[0.9977005,5.00026e-8,0.0006789758,0.0004077432,0.000810819,0.0004019208],"domain_scores_gemma":[0.9972109,0.0001763171,0.0004436084,0.0003465746,0.001694142,0.0001285189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002573477,0.0006937447,0.001116394,0.004044663,0.002959454,6.687349e-7,0.00228688,0.3556894,0.1290675,0.4283703,0.01700692,0.05850671],"study_design_scores_gemma":[0.0004914243,0.0001817392,0.001424646,0.0003703254,0.0003004837,0.00001350532,0.0007129492,0.9867172,0.008330535,0.000213414,0.0009386718,0.0003051252],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9480465,0.0001468262,0.04091508,0.005961024,0.0001248265,0.001667707,0.0001661616,0.0002175924,0.002754286],"genre_scores_gemma":[0.6117226,0.00006026634,0.3874176,0.00007203315,0.0002471443,0.0003196487,0.0000256637,0.00008959816,0.00004546154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6310278,"threshold_uncertainty_score":0.8912924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01418082419882912,"score_gpt":0.2420073624383765,"score_spread":0.2278265382395474,"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."}}