{"id":"W4290790295","doi":"","title":"Hard UV-NIL nanostructures for bimodal SPRI-SERS biosensors","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Gold and Silver Nanoparticles Synthesis and Applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Biosensor; Nanotechnology; Nanostructure; Materials science; Optoelectronics; Computer science","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":[0.0004718933,0.0006066045,0.0006039954,0.000341632,0.0003402172,0.001412753,0.0006996098,0.0009320661,0.005524183],"category_scores_gemma":[0.0006402642,0.0004692562,0.0002689858,0.0001566429,0.0005267122,0.0009663422,0.001168172,0.0009355088,0.002837436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006511966,"about_ca_system_score_gemma":0.000184609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001691065,"about_ca_topic_score_gemma":0.0003760394,"domain_scores_codex":[0.9995601,0.00005105087,0.00002080759,0.0001310399,0.0001630684,0.00007387011],"domain_scores_gemma":[0.9996554,0.0001134907,0.00004670247,0.00004620215,0.00008521003,0.0000530686],"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":[0.00007594942,0.0000213308,0.00004044583,0.0001230285,0.00000503349,0.00002398513,0.00003962331,0.0002663571,0.9937551,0.0005455599,0.0002983983,0.00480516],"study_design_scores_gemma":[0.00001349389,0.0001068521,0.0001954196,0.000007993685,0.000007119182,0.00005918668,0.00003344481,0.004024219,0.9914941,0.0003531575,0.003694046,0.00001099549],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8347468,0.009293198,0.1194736,0.001735602,0.0009767194,0.0002134355,0.0004480934,0.002677516,0.03043504],"genre_scores_gemma":[0.9493124,0.001256537,0.02636084,0.0004055073,0.0001251374,0.0000967961,0.0002116414,0.0003592079,0.02187185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005524183,"threshold_uncertainty_score":0.01848024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01661789884556514,"score_gpt":0.2286858494075144,"score_spread":0.2120679505619493,"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."}}