{"id":"W3212657422","doi":"","title":"Cell imaging with Metal Clad Waveguide (MCWG) Microscopy","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Microscopy; Materials science; Optical microscope; Waveguide; Metal; Optics; Optical imaging; Optoelectronics; Scanning electron microscope; Physics; Metallurgy; Composite material","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":[0.0003037905,0.0004858199,0.0002731695,0.00030781,0.0002408322,0.0006359554,0.000460777,0.0006733432,0.002060448],"category_scores_gemma":[0.0002555212,0.0002679088,0.0002191077,0.0003088205,0.000428777,0.0005208297,0.0006239578,0.0004591039,0.0009310933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006379414,"about_ca_system_score_gemma":0.0002905886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001287912,"about_ca_topic_score_gemma":0.002193837,"domain_scores_codex":[0.9997597,0.00003212375,0.000009708293,0.00007976603,0.00008407739,0.00003471455],"domain_scores_gemma":[0.9997488,0.00008254114,0.00004258842,0.0000531161,0.00004443132,0.00002855518],"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":[0.00004539732,0.000008664882,0.000147962,0.00004892389,0.000004005483,0.0000364423,0.00003311183,0.0005140558,0.9937849,0.001268732,0.0002174533,0.003890327],"study_design_scores_gemma":[0.00001461888,0.000055223,0.0009751102,0.00001059272,0.000007283747,0.0001728134,0.00003650184,0.02276486,0.9689795,0.0007441886,0.006225033,0.00001416103],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7046143,0.002150549,0.2746504,0.0006755544,0.0001831032,0.0001622777,0.0005263317,0.001297756,0.01573958],"genre_scores_gemma":[0.7777783,0.001400113,0.2051023,0.0002990175,0.00006062231,0.0001273028,0.0002483148,0.0001991691,0.01478482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002060448,"threshold_uncertainty_score":0.00689286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006643643341512109,"score_gpt":0.2395693156647915,"score_spread":0.2329256723232794,"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."}}