{"id":"W4413319879","doi":"10.1109/sum65312.2025.11121803","title":"Highly scalable photonic-assisted complex-valued dot product computation method","year":2025,"lang":"en","type":"article","venue":"","topic":"Photonic and Optical Devices","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Photonics; Computer science; Scalability; Computation; Product (mathematics); Dot product; Computational science; Parallel computing; Optoelectronics; Materials science; Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002419656,0.0003197119,0.000379763,0.0002275641,0.0003204434,0.0007174474,0.0008504794,0.0004014577,0.003996641],"category_scores_gemma":[0.0005258351,0.0001633876,0.0002119626,0.0003166165,0.0004966308,0.0008542727,0.000518409,0.0005997316,0.0006359139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004436685,"about_ca_system_score_gemma":0.0006481141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006127403,"about_ca_topic_score_gemma":0.0009395504,"domain_scores_codex":[0.9997621,0.00002595737,0.000009630138,0.0000291592,0.0001421793,0.00003090002],"domain_scores_gemma":[0.9997944,0.00007090252,0.00001687603,0.00004004293,0.00005418861,0.00002350086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003705358,0.000328586,0.0007361918,0.0003449741,0.00009734034,0.0005335021,0.0001828142,0.1228192,0.3521126,0.3935007,0.01038613,0.1185875],"study_design_scores_gemma":[0.00004519406,0.0001111091,0.000115378,0.000007134581,0.00001000379,0.0001038641,0.00001213212,0.9166583,0.06720432,0.01076789,0.004942378,0.00002222705],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1447317,0.0003111257,0.8146738,0.0004225986,0.0002232422,0.000127093,0.0002080032,0.002220989,0.03708144],"genre_scores_gemma":[0.6480018,0.0001156445,0.3474499,0.0001152948,0.00002527858,0.0001150838,0.0001710724,0.000126111,0.003879821],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003996641,"threshold_uncertainty_score":0.0133701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02252357744140203,"score_gpt":0.2909303705730341,"score_spread":0.2684067931316321,"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."}}