{"id":"W2114929409","doi":"10.1364/josaa.27.000319","title":"Particle swarm optimization for ellipsometric data inversion of samples having an arbitrary number of layers","year":2010,"lang":"en","type":"article","venue":"Journal of the Optical Society of America A","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Particle swarm optimization; Inversion (geology); Ellipsometry; Algorithm; Optics; Inverse transform sampling; Computer science; Materials science; Physics; Thin film; Geology; Nanotechnology","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":[0.000390428,0.00009162109,0.0002966454,0.00004212671,0.00004189473,0.00001185436,0.0004690299,0.00009545524,0.0000566005],"category_scores_gemma":[0.0004069716,0.00006876335,0.0002341259,0.0006651969,0.0002350104,0.000317247,0.00008549841,0.0002754225,9.250974e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001870484,"about_ca_system_score_gemma":0.00004001885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001025193,"about_ca_topic_score_gemma":2.901727e-7,"domain_scores_codex":[0.9988913,0.00002297622,0.0005321183,0.00008832896,0.0003117988,0.0001534696],"domain_scores_gemma":[0.9987943,0.000290985,0.0002888503,0.0003202299,0.0001892041,0.0001164386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002850309,0.001869781,0.03106149,0.001258783,0.0009587284,7.47209e-7,0.002165701,0.5918785,0.3299579,0.001900348,0.007971336,0.03069169],"study_design_scores_gemma":[0.0005488964,0.0001535963,0.001760296,0.00005270412,0.0001347346,0.000006098192,0.0005214353,0.9563242,0.03945715,0.0003121998,0.0006175896,0.000111173],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7733415,0.00008568442,0.2254167,0.0005421335,0.000286838,0.0001142591,0.00003994557,0.00001477459,0.0001581112],"genre_scores_gemma":[0.6680199,0.00009421523,0.3317357,0.00006736604,0.00005770679,3.058923e-7,0.00000467369,0.00001391185,0.000006237462],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3644457,"threshold_uncertainty_score":0.2804088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0276843314603808,"score_gpt":0.2754274655986341,"score_spread":0.2477431341382533,"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."}}