{"id":"W2954466838","doi":"10.1038/s41598-019-46060-8","title":"Collapse on the line – how synthetic dimensions influence nonlinear effects","year":2019,"lang":"en","type":"preprint","venue":"Scientific Reports","topic":"Advanced Fiber Laser Technologies","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; Government Council on Grants, Russian Federation; Deutsche Forschungsgemeinschaft; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; 1000 Talents Sichuan Program","keywords":"Nonlinear system; Lattice (music); Physics; Transverse plane; Optics; Instability; Nonlinear optics; Diffraction; Mechanics; Quantum mechanics; Acoustics; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006581332,0.0004126232,0.000430767,0.0001710534,0.0004299264,0.0005227015,0.0006075334,0.0001814166,0.00003986102],"category_scores_gemma":[0.0003577241,0.0002773649,0.0002380981,0.0003978315,0.0005535547,0.00009627646,0.001330896,0.0009614337,0.0001589801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006055412,"about_ca_system_score_gemma":0.0002769533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001983569,"about_ca_topic_score_gemma":0.000002167922,"domain_scores_codex":[0.9970711,0.00007296986,0.0003948654,0.001418571,0.0005874144,0.0004551145],"domain_scores_gemma":[0.9946192,0.0003708733,0.0007172651,0.003959645,0.0002521751,0.00008083112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000105475,0.003038462,0.04542053,0.001341478,0.001627707,0.002431738,0.002152515,0.5169785,0.134635,0.04475437,0.2179815,0.02953277],"study_design_scores_gemma":[0.0003111882,0.000154217,0.0007036827,0.001896321,0.0002549108,0.00003392515,0.0004308464,0.005678962,0.5422278,0.3460617,0.1005583,0.001688146],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843944,0.000133182,0.001408595,0.001645496,0.008985848,0.001711451,0.00004950822,0.0002656741,0.001405794],"genre_scores_gemma":[0.9918651,0.000002483286,0.001461893,0.00004270513,0.0001175856,0.0002204723,0.0001112841,0.00004280807,0.006135696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5112996,"threshold_uncertainty_score":0.9999679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01044320053146245,"score_gpt":0.2454486020794445,"score_spread":0.235005401547982,"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."}}