{"id":"W6948450937","doi":"10.48550/arxiv.2203.00336","title":"Enhanced Image Reconstruction From Quarter Sampling Measurements Using An Adapted Very Deep Super Resolution Network","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sampling (signal processing); Pixel; Image resolution; Masking (illustration); Iterative reconstruction; Image quality; Quarter (Canadian coin); Image sensor","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005936349,0.0005369654,0.0004504455,0.0004539138,0.000128984,0.0005293074,0.0006228043,0.0005322585,0.001292911],"category_scores_gemma":[0.001626067,0.0002784036,0.0003570416,0.0005350005,0.0003817575,0.0009823897,0.000971496,0.0006883312,0.0003687752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003655835,"about_ca_system_score_gemma":0.0003820251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001422255,"about_ca_topic_score_gemma":0.002541607,"domain_scores_codex":[0.9997219,0.00007320247,0.0000115673,0.00006620562,0.00009231588,0.00003474388],"domain_scores_gemma":[0.9995236,0.0001252357,0.00005954396,0.0001408501,0.0001243909,0.00002635392],"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":[0.001174758,0.0001806685,0.003796021,0.0003607174,0.0001861296,0.0004226369,0.0002180342,0.2833544,0.3157902,0.009598168,0.00533676,0.3795815],"study_design_scores_gemma":[0.00001109903,0.00006123494,0.0009906157,0.000008151649,0.00001345707,0.0001275575,0.0000223655,0.9603916,0.03408616,0.002853424,0.00142189,0.00001243144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1141623,0.000323886,0.8813683,0.0002440827,0.00005275654,0.00003142327,0.0005134681,0.001456805,0.001846916],"genre_scores_gemma":[0.5127307,0.0002807377,0.4829687,0.0001490533,0.00002447896,0.00004375374,0.001255729,0.0001539028,0.00239302],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001422255,"threshold_uncertainty_score":0.004325211,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1095574558781436,"score_gpt":0.2126628772683749,"score_spread":0.1031054213902313,"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."}}