{"id":"W2321753895","doi":"10.1021/nl300476d","title":"Tuning the Surface Charge Properties of Epitaxial InN Nanowires","year":2012,"lang":"en","type":"article","venue":"Nano Letters","topic":"GaN-based semiconductor devices and materials","field":"Physics and Astronomy","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Doping; Materials science; Nanowire; Fermi level; Epitaxy; Condensed matter physics; Surface states; Valence (chemistry); Effective mass (spring–mass system); Electron; Nanotechnology; Optoelectronics; Chemistry; Surface (topology); 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":[0.0001309018,0.0002088196,0.0001876113,0.00009142833,0.0001207576,0.0003951389,0.0002023041,0.0001466346,0.0004124056],"category_scores_gemma":[0.0003242806,0.0001472276,0.00008251659,0.0001178587,0.0001340505,0.0002260166,0.0001387448,0.0001635887,0.0001044738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002095132,"about_ca_system_score_gemma":0.00008258154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000504012,"about_ca_topic_score_gemma":0.001179062,"domain_scores_codex":[0.9998965,0.000008205144,0.000007473498,0.00002118741,0.00004359434,0.00002292262],"domain_scores_gemma":[0.9998738,0.00003984295,0.00003396608,0.00001262704,0.00002728785,0.00001253292],"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":[0.00002775603,0.000009841187,0.0005012125,0.00001902386,0.000003459501,0.00002782918,0.0000130957,0.0002877764,0.9982539,0.00009184118,0.00001724123,0.0007470602],"study_design_scores_gemma":[0.000008659411,0.00008661934,0.0041434,0.000003209793,0.000007512278,0.00003522655,0.00002386307,0.004738877,0.9905496,0.00004309565,0.0003543869,0.000005518048],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988186,0.00009348446,0.0003418626,0.00001460131,0.000005495377,0.000002761987,0.00003937207,0.00001097481,0.0006728029],"genre_scores_gemma":[0.9987948,0.00009631704,0.0006732541,0.000008638848,0.0000035321,0.000004276768,0.00006040728,0.0000125913,0.000346161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000504012,"threshold_uncertainty_score":0.001520097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02184058460423709,"score_gpt":0.2235849050080835,"score_spread":0.2017443204038464,"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."}}