{"id":"W2049398204","doi":"10.1117/12.843712","title":"Dry etched nanoporous silicon substrates for optical biosensors","year":2010,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Silicon Nanostructures and Photoluminescence","field":"Materials Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Porous silicon; Materials science; Silicon; Substrate (aquarium); Biosensor; Nanoporous; Etching (microfabrication); Optoelectronics; Dry etching; Nanotechnology; Silicon dioxide; Fabrication; Hybrid silicon laser; Photoresist; Xenon difluoride; Layer (electronics); Composite material; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007542044,0.000405015,0.0005243789,0.00008591907,0.000142255,0.0002228138,0.00127356,0.0003641098,0.00005948739],"category_scores_gemma":[0.001207961,0.0003254653,0.0006599721,0.0002584567,0.0005204992,0.0004797458,0.0001529921,0.000385013,0.000003826596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006575562,"about_ca_system_score_gemma":0.00006049986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002691976,"about_ca_topic_score_gemma":0.000001459783,"domain_scores_codex":[0.997332,1.423706e-8,0.0008109079,0.0005857383,0.0006655543,0.0006057872],"domain_scores_gemma":[0.9971858,0.0003305965,0.0004216933,0.0001014067,0.001756446,0.0002040155],"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":[0.0001396177,0.00008273629,0.0006100995,0.0002977855,0.00007931128,9.326121e-8,0.0001362509,0.00001282493,0.7633682,0.2343973,0.0007578693,0.0001178493],"study_design_scores_gemma":[0.0009405411,0.0002767441,0.001615186,0.00009726173,0.00009747865,0.0000182036,0.0005813334,0.004979755,0.9881034,0.001622323,0.001296924,0.0003707898],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958879,0.00005169598,0.000005690175,0.001460251,0.0009373559,0.0008458137,0.0001292807,0.000119111,0.0005628819],"genre_scores_gemma":[0.9310048,0.00002497444,0.06778001,0.0001186706,0.0006475751,0.0001910945,0.00001159958,0.00006952532,0.0001517345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.232775,"threshold_uncertainty_score":0.9999197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009737110542649875,"score_gpt":0.2308405302147728,"score_spread":0.221103419672123,"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."}}