{"id":"W4410518734","doi":"10.1021/acsphotonics.5c00505","title":"Scalable Freeform Optimization of Wide-Aperture 3D Metalenses by Zoned Discrete Axisymmetry","year":2025,"lang":"en","type":"article","venue":"ACS Photonics","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Army Research Office; Simons Foundation; Naval Air Warfare Center, Aircraft Division; U.S. Department of Energy","keywords":"Materials science; Optics; Aperture (computer memory); Scalability; Computer science; Optoelectronics; Physics; Acoustics","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":[0.0005217885,0.0001863392,0.0004060141,0.00007020817,0.0001714348,0.00008234665,0.0003965169,0.0001332953,0.0007624907],"category_scores_gemma":[0.0002754832,0.0001511191,0.00007158187,0.0004179969,0.000117672,0.0002270283,0.0001366914,0.00007392512,0.0000499837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003800567,"about_ca_system_score_gemma":0.00008703989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001720156,"about_ca_topic_score_gemma":0.00001533405,"domain_scores_codex":[0.9985659,0.00006689216,0.0004963192,0.0003491739,0.0002499386,0.0002718402],"domain_scores_gemma":[0.9987373,0.0001753147,0.0002476524,0.0006248245,0.0001512977,0.00006362886],"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":[0.0000266226,0.00006698423,0.00005178677,0.0000783741,0.00003094178,2.518161e-7,0.00005816616,0.002352605,0.9908193,0.001204894,0.005209051,0.0001010056],"study_design_scores_gemma":[0.0003079992,0.00003363056,0.00003926549,0.00003176812,0.0001056254,0.000001067862,0.00006731625,0.005178404,0.9455376,0.0002693649,0.04827033,0.0001576088],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9645519,0.002192121,0.02621559,0.0004787629,0.0004784919,0.0005779138,0.000543017,0.0001037409,0.004858476],"genre_scores_gemma":[0.8848358,0.001323981,0.1086176,0.000999504,0.00001643551,0.0001474897,0.0003419215,0.00003945245,0.003677737],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08240205,"threshold_uncertainty_score":0.8348739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007342273386568886,"score_gpt":0.2440347746515993,"score_spread":0.2366925012650304,"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."}}