{"id":"W2151620395","doi":"10.1109/ccece.1995.528118","title":"The general unknown parameter receiver","year":2002,"lang":"en","type":"article","venue":"","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Intersymbol interference; Demodulation; Computer science; Offset (computer science); Frequency offset; Channel (broadcasting); Detection theory; Interference (communication); Electronic engineering; Adjacent-channel interference; Noise (video); Radio receiver design; Algorithm; Telecommunications; Orthogonal frequency-division multiplexing; Engineering; Detector; Artificial intelligence; Transmitter","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":[0.001108112,0.0007924988,0.0008134112,0.0003582872,0.0003967032,0.001086214,0.001660225,0.001807934,0.002577249],"category_scores_gemma":[0.00187021,0.0004285398,0.0007411696,0.0005418334,0.0009770511,0.00196462,0.000977667,0.001296563,0.002561776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006307263,"about_ca_system_score_gemma":0.001020188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005672884,"about_ca_topic_score_gemma":0.0006209645,"domain_scores_codex":[0.999137,0.0001969025,0.00003672199,0.0002054701,0.000334641,0.00008927628],"domain_scores_gemma":[0.9994484,0.0001406931,0.00005742677,0.0001745452,0.0001592341,0.00001979018],"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":[0.0003041779,0.0001173334,0.001179719,0.0004269651,0.0001785057,0.0005186619,0.0002587737,0.3346153,0.0848769,0.3238914,0.007399515,0.2462327],"study_design_scores_gemma":[0.00006651129,0.0003840512,0.0005055164,0.00005684169,0.0001274906,0.001207191,0.0000347136,0.8325298,0.03818256,0.06142075,0.06537936,0.000105101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002212401,0.0001982985,0.9948055,0.00007337081,0.0000474507,0.00003811415,0.00002856941,0.0002473838,0.002348926],"genre_scores_gemma":[0.1595303,0.001171556,0.8262593,0.0003726151,0.0003183402,0.0001914767,0.0002042719,0.00008603534,0.01186605],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002577249,"threshold_uncertainty_score":0.008621752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01835239344338045,"score_gpt":0.2203558618132216,"score_spread":0.2020034683698411,"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."}}