{"id":"W2938807164","doi":"10.1051/epjconf/201920501012","title":"Peak power & average power scaling via fourier domain OPA (FOPA)","year":2019,"lang":"en","type":"article","venue":"EPJ Web of Conferences","topic":"Laser-Matter Interactions and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Joint Attosecond Science Laboratory; Institut National de la Recherche Scientifique","funders":"","keywords":"Fourier transform; Boosting (machine learning); Scaling; Power (physics); Fourier domain; Frequency domain; Physics; Computer science; Optics; Materials science; Mathematics; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001100375,0.0001431538,0.0002113101,0.00006171199,0.00008279829,0.00007931571,0.0002320628,0.00003258355,0.02884821],"category_scores_gemma":[0.000002125649,0.0001209451,0.0001196336,0.0001045722,0.00004788781,0.0001670769,0.00005789672,0.0001406998,0.001139546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007936795,"about_ca_system_score_gemma":0.0001598485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001744752,"about_ca_topic_score_gemma":0.00001225212,"domain_scores_codex":[0.9991024,0.00003074338,0.000271375,0.0002293414,0.0001723387,0.0001938631],"domain_scores_gemma":[0.9992282,0.00007992763,0.0001573257,0.0003567057,0.0001119337,0.00006586309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006191726,0.0009952575,0.2662856,0.00004081335,0.0005192746,0.000001595391,0.001758361,0.0002502388,0.07306668,0.6313645,0.01803522,0.007620558],"study_design_scores_gemma":[0.0008747023,0.00008782641,0.01947055,0.0001276489,0.00004094116,0.000002897123,0.001225082,0.0005780171,0.009540078,0.03628297,0.9312211,0.0005481758],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7385235,0.00001027269,0.01507355,0.000451617,0.0002515439,0.0001650428,0.00005547586,0.00001916991,0.2454498],"genre_scores_gemma":[0.9951508,7.86713e-7,0.0008780839,0.00007404867,0.00008162731,0.00002672666,0.00004094327,0.00001186046,0.003735115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9131859,"threshold_uncertainty_score":0.9996382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009977612475968067,"score_gpt":0.2567745174128439,"score_spread":0.2467969049368758,"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."}}