{"id":"W2085892268","doi":"10.1364/oe.22.026103","title":"Tailoring the refractive index of Ge-S based glass for 3D embedded waveguides operating in the mid-IR region","year":2014,"lang":"en","type":"article","venue":"Optics Express","topic":"Laser Material Processing Techniques","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Materials science; Refractive index; Raman spectroscopy; Femtosecond; Optics; Refractometry; Laser; Fabrication; Irradiation; High-refractive-index polymer; Photonics; Optoelectronics","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":[0.0005725145,0.0001411694,0.000171731,0.00004795536,0.00008678878,0.0001048626,0.0003961792,0.00008539693,0.000001743317],"category_scores_gemma":[0.000253534,0.00009155612,0.00003546605,0.0001016235,0.00005130301,0.0001576849,0.0000456223,0.0001487525,5.365479e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003758411,"about_ca_system_score_gemma":0.00001478145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002857746,"about_ca_topic_score_gemma":0.000004795328,"domain_scores_codex":[0.9991666,0.00007303601,0.0002720242,0.0001414445,0.0001455011,0.0002013862],"domain_scores_gemma":[0.9990513,0.0003818187,0.00007877666,0.0003898849,0.00008051171,0.00001770904],"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":[0.0001229968,0.0001234456,0.0004615146,0.001426423,0.0000538415,0.00000721353,0.009121572,0.2086318,0.7670106,0.003187539,0.00164243,0.008210615],"study_design_scores_gemma":[0.0002922222,0.00004245181,0.00008481037,0.0002052629,0.00001206298,0.000001522829,0.0002287865,0.5550142,0.4419188,0.000971313,0.001093209,0.0001353286],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4804491,0.00005102528,0.5130256,0.0002713976,0.000313158,0.0007741791,0.00001028089,0.0003013211,0.004803827],"genre_scores_gemma":[0.9575669,0.000005498911,0.04202019,0.00006909598,0.0001197369,0.0001625666,0.000004741628,0.00003740854,0.00001389305],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4771177,"threshold_uncertainty_score":0.373355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0208157318023907,"score_gpt":0.2542963256686275,"score_spread":0.2334805938662368,"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."}}