{"id":"W4322738845","doi":"10.1038/s41598-023-30516-z","title":"Resolving hidden pixels beyond the resolution limit of projection imaging by square aperture","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Ministerio de Ciencia e Innovación; Austrian Science Fund; McMaster University","keywords":"Pixel; Computer science; Limit (mathematics); Projection (relational algebra); Aperture (computer memory); Optics; Square (algebra); Ghost imaging; Resolution (logic); Image resolution; Computer vision; Coded aperture; Artificial intelligence; Physics; Algorithm; Mathematics; Geometry; Detector; Mathematical analysis; Acoustics","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":[0.0006904016,0.0006944156,0.0005922192,0.000317852,0.0002986757,0.0009627742,0.0006695677,0.0008683918,0.001589115],"category_scores_gemma":[0.00162268,0.0004027485,0.0003883535,0.0003970095,0.001268123,0.001680323,0.001622717,0.001061584,0.0006785335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002711399,"about_ca_system_score_gemma":0.0004325171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002523017,"about_ca_topic_score_gemma":0.0003099517,"domain_scores_codex":[0.9995577,0.00006618098,0.00002323437,0.0001223441,0.0001895586,0.00004095815],"domain_scores_gemma":[0.9991555,0.0003487082,0.0001223325,0.0001858499,0.0001302665,0.00005733466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004441842,0.00008626961,0.001714684,0.0007060441,0.00006126655,0.0008410797,0.000674645,0.03113484,0.6930822,0.1280174,0.002003432,0.1412341],"study_design_scores_gemma":[0.00008532764,0.0004556525,0.001280357,0.00008731223,0.00007047131,0.002438368,0.0001558077,0.5651281,0.3657707,0.0464123,0.01798659,0.0001289059],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04429753,0.0008730238,0.949423,0.00020478,0.00007437514,0.00005453719,0.00004618133,0.0003768551,0.004649724],"genre_scores_gemma":[0.3562889,0.001103376,0.6392097,0.0002190578,0.00006662188,0.00008562367,0.00009186965,0.00009858421,0.002836073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001589115,"threshold_uncertainty_score":0.005316138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009550615048533986,"score_gpt":0.2620995010879696,"score_spread":0.2525488860394356,"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."}}