{"id":"W2591951130","doi":"10.1117/12.2251562","title":"Tailoring the refractive index of ITO thin films by genetic algorithm optimization of the reactive DC-sputtering parameters","year":2017,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"ZnO doping and properties","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Refractive index; Sputtering; Thin film; Materials science; Deposition (geology); Indium tin oxide; Analytical Chemistry (journal); Sputter deposition; Algorithm; Optoelectronics; Optics; Computer science; Nanotechnology; Physics; Chemistry","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":[0.0002909049,0.0005275284,0.0002408515,0.0003400651,0.0001475631,0.0003884122,0.0003373518,0.0003308138,0.0002499178],"category_scores_gemma":[0.0008494026,0.0001912826,0.0002810297,0.0003108185,0.0002002978,0.0002076543,0.000156003,0.0002300382,0.00007082267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000438982,"about_ca_system_score_gemma":0.0004022637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001617725,"about_ca_topic_score_gemma":0.00254623,"domain_scores_codex":[0.9998854,0.0000184576,0.000006055037,0.00003196014,0.00003760406,0.00002054089],"domain_scores_gemma":[0.9997522,0.0001038961,0.00006133736,0.00001834356,0.0000557185,0.000008325329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000177053,0.0001354985,0.006381749,0.0001860706,0.00009289881,0.0001233403,0.0001213547,0.6439413,0.2914869,0.001234089,0.000363272,0.05575651],"study_design_scores_gemma":[0.00002014397,0.0001324507,0.002803557,0.000007977302,0.00003982475,0.0000414403,0.00003245049,0.9145043,0.08146563,0.000301948,0.0006346951,0.00001555326],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8724919,0.0005527596,0.1230244,0.0001182205,0.00002845247,0.00006083015,0.00007869087,0.0003190228,0.003325679],"genre_scores_gemma":[0.930285,0.000182899,0.06879161,0.00002443789,0.000004215124,0.00006646506,0.00005930102,0.000045813,0.0005402927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001617725,"threshold_uncertainty_score":0.003216624,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.014598633715877,"score_gpt":0.2303250551454513,"score_spread":0.2157264214295743,"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."}}