{"id":"W4406900980","doi":"10.1117/12.3048947","title":"Three-dimensional femtosecond laser beam shaping by real-time training and inference of a physics informed machine learning model","year":2025,"lang":"en","type":"article","venue":"","topic":"Laser Material Processing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Femtosecond; Laser beams; Inference; Laser; Beam (structure); Computer science; Physics; Artificial intelligence; Optics; Machine learning","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":[0.0001146254,0.0001576885,0.0002426973,0.00006346549,0.00005800876,0.00004452878,0.0001005479,0.0000792526,0.00004667163],"category_scores_gemma":[0.00004573726,0.0001500257,0.00002304309,0.0001224633,0.00004959978,0.0002612871,0.0000931981,0.0001466067,0.000002104975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002755068,"about_ca_system_score_gemma":0.00006092056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008775858,"about_ca_topic_score_gemma":0.000025157,"domain_scores_codex":[0.9993208,0.000005317698,0.0002518626,0.0001386528,0.00009999381,0.0001833421],"domain_scores_gemma":[0.9996857,0.00008500984,0.00004397014,0.0001066352,0.00004111701,0.00003754563],"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":[0.00004379799,0.00004244218,0.0007471365,0.001082352,0.0001323843,0.000001502579,0.00106883,0.2529479,0.7098047,0.001669234,0.003253015,0.02920673],"study_design_scores_gemma":[0.0002096354,0.00001967655,0.00003778209,0.0001740944,0.00001122461,5.633602e-7,0.000008766033,0.8182859,0.1760233,0.005034805,0.00005190277,0.00014239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8873206,0.00009543831,0.1024715,0.00003033004,0.00003704524,0.0001450388,0.00002968912,0.001014277,0.008856052],"genre_scores_gemma":[0.9784878,0.00002821908,0.0210645,0.00005175708,0.000009879659,0.00001163707,0.00003667805,0.00002338467,0.0002860785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.565338,"threshold_uncertainty_score":0.6117873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0211147417974381,"score_gpt":0.2495802294817547,"score_spread":0.2284654876843166,"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."}}