{"id":"W1652571342","doi":"10.1002/sdtp.10449","title":"35.3: Resolution Enhancement Based on Shifted Superposition","year":2015,"lang":"en","type":"article","venue":"SID Symposium Digest of Technical Papers","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Christie (Canada); University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Ontario Ministry of Economic Development and Innovation","keywords":"Resolution (logic); Superposition principle; Projection (relational algebra); Projector; Set (abstract data type); Computer science; High resolution; Image (mathematics); Artificial intelligence; Image resolution; Computer vision; Mathematics; Algorithm; Remote sensing; Geology; Mathematical analysis","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":[0.0006348705,0.0008577176,0.0006229102,0.0006590503,0.0003002529,0.0006932225,0.001291191,0.0006275328,0.003304933],"category_scores_gemma":[0.001050229,0.000373493,0.0008414849,0.0005717466,0.000671038,0.00124481,0.001596889,0.0008247835,0.0008829865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004070262,"about_ca_system_score_gemma":0.0007411993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001248322,"about_ca_topic_score_gemma":0.001643563,"domain_scores_codex":[0.9992574,0.0001084352,0.00002710377,0.0001197094,0.0004273552,0.00005984938],"domain_scores_gemma":[0.9995852,0.00008594228,0.00004871444,0.000128645,0.0001153649,0.0000361544],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004749603,0.00022665,0.001819612,0.0002175916,0.0001995167,0.0003481757,0.0001802404,0.1095762,0.4233702,0.02159101,0.003108025,0.4388878],"study_design_scores_gemma":[0.00004563227,0.0002821695,0.001511311,0.00001687321,0.00008916967,0.0008643193,0.00003145963,0.7697926,0.2147599,0.006432962,0.006122011,0.00005160685],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05281011,0.0004113413,0.9380245,0.0001725383,0.00003640163,0.00007266153,0.00006571337,0.001878789,0.006527898],"genre_scores_gemma":[0.4453568,0.0004868124,0.5471405,0.0002355493,0.00004144734,0.00008767844,0.0003132639,0.0002781288,0.00605984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003304933,"threshold_uncertainty_score":0.01105607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01287398415740771,"score_gpt":0.2330285786157704,"score_spread":0.2201545944583627,"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."}}