{"id":"W2999091750","doi":"10.1002/adfm.201907357","title":"Exploiting Phonon‐Resonant Near‐Field Interaction for the Nanoscale Investigation of Extended Defects","year":2020,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Near-Field Optical Microscopy","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"U.S. Naval Research Laboratory; Office of Naval Research; Ministerium für Innovation, Wissenschaft und Forschung des Landes Nordrhein-Westfalen; Deutsche Forschungsgemeinschaft","keywords":"Materials science; Semiconductor; Near-field scanning optical microscope; Phonon; Nanoscopic scale; Photonics; Photoluminescence; Optoelectronics; Infrared; Terahertz radiation; Optics; Nanotechnology; Optical microscope; Scanning electron microscope; Condensed matter physics; Physics","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":[0.0001466666,0.0001554994,0.00008901402,0.0004041267,0.000161047,0.0001803029,0.0002247849,0.0002533672,0.001049104],"category_scores_gemma":[0.000155951,0.00008977491,0.00008647211,0.0001113262,0.0003123912,0.0002496578,0.0002125691,0.000277881,0.0001171704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001808121,"about_ca_system_score_gemma":0.0001207654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002978951,"about_ca_topic_score_gemma":0.0007075041,"domain_scores_codex":[0.9999326,0.000009311186,0.000001989214,0.00001515757,0.00002874099,0.00001217479],"domain_scores_gemma":[0.9998775,0.00005164919,0.00002584614,0.00001263949,0.00002095145,0.00001138787],"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":[0.00001947352,0.00001715215,0.0004765002,0.00003193293,0.000002706679,0.00003188613,0.0000259459,0.000220443,0.9953511,0.0006415063,0.00007255703,0.003108749],"study_design_scores_gemma":[0.000008739577,0.0001388574,0.00477432,0.00001035151,0.000006720085,0.0002319958,0.00009642362,0.01479775,0.9779072,0.0005779581,0.001438007,0.0000116685],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826337,0.0005002108,0.01361158,0.00005291465,0.00002109968,0.00001540812,0.00005110209,0.0001025272,0.003011491],"genre_scores_gemma":[0.9893767,0.0001518554,0.009504829,0.00002671088,0.000006861983,0.00001432281,0.00002576349,0.000007983152,0.0008850501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001049104,"threshold_uncertainty_score":0.003509581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02214050455291821,"score_gpt":0.2367818189534973,"score_spread":0.2146413144005791,"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."}}