{"id":"W4287896669","doi":"10.1364/ecbo.2021.es1a.2","title":"Unmatched Back Projector Deconvolution for a Miniature Light Field Microscope","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"","keywords":"Projector; Deconvolution; Optics; Light field; Microscope; Structured light; Depth of field; Microscopy; Field (mathematics); Optical microscope; Light sheet fluorescence microscopy; Materials science; Computer vision; Laser; Computer science; Artificial intelligence; Computer graphics (images); Physics; Mathematics; Scanning confocal electron microscopy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005454803,0.0001411143,0.0001278058,0.00001871271,0.00005453517,0.00002644079,0.0001307901,0.0002505559,0.00009618208],"category_scores_gemma":[0.0001372961,0.0001323908,0.00009727151,0.00008037544,0.00002358628,0.000004736302,0.00008710985,0.00007063175,0.00001480995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001708048,"about_ca_system_score_gemma":0.0001282874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004007467,"about_ca_topic_score_gemma":0.00008004496,"domain_scores_codex":[0.9991434,0.00001931557,0.0001585884,0.0003917676,0.00004691092,0.0002399769],"domain_scores_gemma":[0.9993905,0.00001338302,0.00004808605,0.0003349565,0.000165544,0.00004753767],"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":[0.00007347791,0.00004177204,0.0002968148,0.00003469941,0.00001599836,0.000001285222,0.00001992346,4.177293e-7,0.9408582,0.00007959908,0.05794049,0.0006373149],"study_design_scores_gemma":[0.0002615984,0.0002289219,0.00003498846,0.00001820428,0.00000717828,0.00001113636,0.00004134167,0.00001085688,0.8162274,0.0000896819,0.1829202,0.000148438],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1987135,0.003049073,0.788189,0.003109575,0.0005583451,0.001527064,0.0000982688,0.0001470577,0.004608158],"genre_scores_gemma":[0.07894854,0.0003089625,0.895495,0.003666374,0.0004019156,0.0002058084,0.0004947652,0.00006276677,0.02041588],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1249798,"threshold_uncertainty_score":0.5398742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007723681214351153,"score_gpt":0.2914652536449555,"score_spread":0.2837415724306044,"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."}}