{"id":"W2911454361","doi":"10.1364/oe.27.002488","title":"Spatially resolved cross-sectional refractive index profile of fs laser–written waveguides using a genetic algorithm","year":2019,"lang":"en","type":"article","venue":"Optics Express","topic":"Laser Material Processing Techniques","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Optics; Laser; Interferometry; Refractive index; Femtosecond; Waveguide; Materials science; Mach–Zehnder interferometer; Refractive index profile; Measure (data warehouse); Photonics; Physics; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001447097,0.0002021725,0.0002528172,0.0001055092,0.0000513917,0.0001241158,0.0002706327,0.0001929243,0.0001221698],"category_scores_gemma":[0.00003247416,0.0002113157,0.00005454723,0.0001214728,0.00007451327,0.0002672777,0.0001237622,0.0001724613,0.00001784313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001010346,"about_ca_system_score_gemma":0.00005767432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009352966,"about_ca_topic_score_gemma":0.000001162907,"domain_scores_codex":[0.9987385,0.00002665637,0.0004091354,0.0002599564,0.0002961818,0.0002695833],"domain_scores_gemma":[0.9991809,0.00004603107,0.0001196855,0.0003668875,0.0002270469,0.00005945166],"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":[0.0001084919,0.0001025693,0.0111566,0.0006828386,0.0001557337,0.00002043553,0.000394365,0.1231533,0.8615056,0.00006470549,0.0001468342,0.002508523],"study_design_scores_gemma":[0.0003630402,0.00006056525,0.00880614,0.0001236488,0.00001514885,0.00001132879,0.00001452949,0.4528813,0.5366064,0.0006272626,0.0002106242,0.0002799438],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8957928,0.00004472605,0.1005737,0.000002784531,0.0004283295,0.0003298864,0.00009863676,0.0003522565,0.002376914],"genre_scores_gemma":[0.7400581,0.000009465764,0.2595271,0.000007621447,0.0001354215,0.0000220349,0.00001873792,0.00006299158,0.0001584574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.329728,"threshold_uncertainty_score":0.8617203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01514249185603436,"score_gpt":0.2608607041755857,"score_spread":0.2457182123195513,"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."}}