{"id":"W2005528754","doi":"10.1109/tip.2012.2188810","title":"Binned Progressive Quantization for Compressive Sensing","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Encoder; Quantization (signal processing); Computer science; Compressed sensing; Algorithm; Data compression; Decoding methods; Distributed source coding; Electronic engineering; Channel code; Engineering","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":[0.0006062941,0.0004063859,0.0003233828,0.0004257009,0.0002080628,0.0004804243,0.0005868085,0.0004833931,0.002295494],"category_scores_gemma":[0.002267002,0.0001615799,0.0001855259,0.001027019,0.0007021945,0.000859497,0.0006869029,0.001178532,0.0004393139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004477484,"about_ca_system_score_gemma":0.0006110476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001126446,"about_ca_topic_score_gemma":0.001614787,"domain_scores_codex":[0.9995254,0.0001272357,0.00002067391,0.00006688975,0.0002401876,0.00001952787],"domain_scores_gemma":[0.9995207,0.0002383919,0.00004242096,0.00009808098,0.00008437009,0.00001610714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002516274,0.00005040858,0.0003663836,0.0004145809,0.00003383504,0.0001742244,0.0001746536,0.1469603,0.07001489,0.3055663,0.005479755,0.470513],"study_design_scores_gemma":[0.00003373317,0.0001675597,0.0004082408,0.0001058643,0.00001884727,0.0003258308,0.00004812095,0.8406967,0.02826521,0.1075454,0.02234106,0.00004332135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004945147,0.002013555,0.9897127,0.0002478418,0.0001199841,0.00004923667,0.00006153575,0.0002319413,0.002618014],"genre_scores_gemma":[0.3147613,0.004212983,0.6750302,0.0004003372,0.0002194272,0.0001480327,0.0002647531,0.0000681871,0.004894745],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002295494,"threshold_uncertainty_score":0.007679164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02231883729748058,"score_gpt":0.2708660088469465,"score_spread":0.2485471715494659,"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."}}