{"id":"W4386428075","doi":"10.1109/cleo/europe-eqec57999.2023.10232633","title":"Post-2000 Nonlinear Optical Materials and their Characterization: Data Tables and Best Practices","year":2023,"lang":"en","type":"article","venue":"","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Optical materials; Context (archaeology); Characterization (materials science); Nonlinear optics; Nonlinear optical; Field (mathematics); Nonlinear system; Set (abstract data type); Metamaterial; Computer science; Optical fiber; 3D optical data storage; Engineering physics; Materials science; Optics; Optoelectronics; Nanotechnology; Engineering; Physics; Telecommunications; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0132469,0.003293114,0.002165309,0.03199118,0.001231076,0.0043421,0.003836367,0.00224729,0.05273243],"category_scores_gemma":[0.04868446,0.001189403,0.001611823,0.02563726,0.000996555,0.005221126,0.002620385,0.002533212,0.04764169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002416637,"about_ca_system_score_gemma":0.004375944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003216587,"about_ca_topic_score_gemma":0.003630194,"domain_scores_codex":[0.9868643,0.001674621,0.004334486,0.001074739,0.00545539,0.0005965554],"domain_scores_gemma":[0.919152,0.0301347,0.01030058,0.01089024,0.02832406,0.001198458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001336986,0.0007198646,0.008617138,0.02326439,0.0002508455,0.0005902934,0.0003812493,0.003497925,0.02152894,0.01697438,0.5921482,0.3306897],"study_design_scores_gemma":[0.00005622421,0.0001903283,0.004325218,0.002518673,0.00008346583,0.0003452082,0.0002328787,0.0006898575,0.01692962,0.005994421,0.968533,0.0001010582],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.008963925,0.01423423,0.03787592,0.002165316,0.0008289748,0.001892657,0.8825752,0.01111321,0.04035065],"genre_scores_gemma":[0.01804256,0.016846,0.1353863,0.002118604,0.0003019513,0.004791771,0.8070638,0.002862301,0.01258675],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.05273243,"threshold_uncertainty_score":0.1764076,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03893170958459323,"score_gpt":0.2740146062410677,"score_spread":0.2350828966564744,"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."}}