{"id":"W2016591240","doi":"10.1109/tnano.2014.2310811","title":"Introduction to the special section on the Fifth IEEE International Nanoelectronics Conference (IEEE INEC)","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Nanotechnology","topic":"Semiconductor materials and devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Nanoelectronics; Special section; Session (web analytics); Engineering; Telecommunications; Computer science; Library science; Nanotechnology; Engineering physics; Materials science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000220468,0.0002036969,0.0001660039,0.0002187839,0.0002217444,0.00007342884,0.0004183123,0.0002470976,0.0005709078],"category_scores_gemma":[0.0000199945,0.0001407661,0.00006555645,0.0003081303,0.0000741955,0.00009548025,0.000001829731,0.0005292128,0.000389725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001585545,"about_ca_system_score_gemma":0.00002069365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000264691,"about_ca_topic_score_gemma":0.0003627258,"domain_scores_codex":[0.9989406,0.00005791332,0.0002400896,0.0002928209,0.0001892991,0.0002792597],"domain_scores_gemma":[0.9992952,0.00010157,0.00004649934,0.0004576737,0.00006737934,0.00003165076],"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":[0.0001071115,0.00007446679,7.094809e-7,0.00001179657,0.000106709,7.879876e-7,0.000363901,0.1275099,0.8177251,0.004217416,0.02184646,0.02803565],"study_design_scores_gemma":[0.0001851074,0.0002216064,0.000006888917,0.00001271528,0.00001815941,0.00002230832,0.00006404782,0.006905542,0.7261011,0.0004121553,0.2658864,0.0001640291],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7709172,0.00001055868,0.1842056,0.01443423,0.02904248,0.0003200005,0.0000241627,0.0005589408,0.0004868152],"genre_scores_gemma":[0.9935668,0.00009525633,0.00006386558,0.0004208396,0.005506741,0.0001076034,0.000002777955,0.00003164701,0.0002045364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2440399,"threshold_uncertainty_score":0.6251041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01305364004847928,"score_gpt":0.2149523654272847,"score_spread":0.2018987253788054,"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."}}