{"id":"W2211205266","doi":"","title":"A thermal-Aware Laser Tuning Approach for Silicon Photonic Interconnects","year":2016,"lang":"en","type":"preprint","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"JDA Software (Canada)","funders":"","keywords":"Optoelectronics; Photonics; Resonator; Silicon photonics; Laser; Materials science; Interconnection; Silicon; Wavelength; Optical interconnect; Chip; Photonic integrated circuit; Semiconductor laser theory; Hybrid silicon laser; Electronic engineering; Computer science; Optics; Semiconductor; Physics; Engineering; Telecommunications","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":[0.0001940952,0.000346287,0.0003611391,0.0002461035,0.000454251,0.0006254241,0.0009892323,0.0005871374,0.002763067],"category_scores_gemma":[0.0003925232,0.0002669023,0.0003861815,0.0002552959,0.0003396152,0.0006734802,0.00058749,0.0004691354,0.0004667462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004534305,"about_ca_system_score_gemma":0.0003293508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007945028,"about_ca_topic_score_gemma":0.002809901,"domain_scores_codex":[0.9997633,0.00003407656,0.000007597079,0.00006769058,0.00009630063,0.00003100319],"domain_scores_gemma":[0.9998137,0.00006307272,0.0000238832,0.00004474919,0.00004269652,0.00001191809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000150378,0.0001622384,0.0004818092,0.0001452491,0.00006701201,0.0001275806,0.0001164464,0.2449595,0.6072316,0.01522846,0.001818577,0.1295111],"study_design_scores_gemma":[0.000005451665,0.00005385622,0.000228776,0.000005926261,0.00001817868,0.00006962557,0.00001951702,0.9548416,0.03890037,0.003339921,0.002503762,0.00001308977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07719789,0.0008605902,0.9051873,0.0002555455,0.0001083805,0.00003867918,0.00004454244,0.001075222,0.01523188],"genre_scores_gemma":[0.8469291,0.0003991008,0.1423739,0.0001801489,0.00009497246,0.0000479674,0.00004695832,0.0002102506,0.009717559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002763067,"threshold_uncertainty_score":0.009243369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01278567887444507,"score_gpt":0.2231238947773727,"score_spread":0.2103382159029276,"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."}}