{"id":"W1658626255","doi":"10.1109/ccece.1995.528066","title":"Numerical optimization for CDMA spreading sequences","year":2002,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Code division multiple access; Spread spectrum; Gold code; Computer science; Interference (communication); Sequence (biology); Code (set theory); Set (abstract data type); Algorithm; Selection (genetic algorithm); Direct-sequence spread spectrum; Signal-to-noise ratio (imaging); Noise (video); Electronic engineering; Telecommunications; Engineering; Channel (broadcasting); Artificial intelligence","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":[0.00097833,0.0006338161,0.0005586341,0.0005713277,0.0003896599,0.0007150635,0.0004048613,0.0007940914,0.002816585],"category_scores_gemma":[0.005299366,0.000301868,0.0003557831,0.0006030713,0.0006761218,0.0004928001,0.000709086,0.0006524347,0.0004862745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008618265,"about_ca_system_score_gemma":0.0009697829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004131109,"about_ca_topic_score_gemma":0.002834636,"domain_scores_codex":[0.9996837,0.0001445162,0.0000140654,0.00003054485,0.00009618439,0.00003097413],"domain_scores_gemma":[0.9982812,0.001178795,0.0001127073,0.00008028025,0.0003051203,0.00004193461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003083438,0.00001479004,0.0002084959,0.00005233312,0.000008727387,0.00002932734,0.00002169939,0.9762526,0.000886852,0.01482804,0.0004690592,0.007197198],"study_design_scores_gemma":[0.000009332353,0.000006257055,0.00003541957,0.000005758248,0.000001814986,0.000004446634,0.000004871968,0.9959763,0.0002492614,0.003209859,0.0004942453,0.000002572825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05475792,0.001162032,0.9178053,0.0007964912,0.0001350053,0.0001379127,0.0002243359,0.0002670492,0.02471408],"genre_scores_gemma":[0.5214192,0.0006922971,0.4678397,0.0001849266,0.00005359091,0.0006005461,0.0003215077,0.0001625549,0.008725712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004131109,"threshold_uncertainty_score":0.009422421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06944134569070023,"score_gpt":0.3009823642616362,"score_spread":0.231541018570936,"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."}}