{"id":"W6993190959","doi":"","title":"Novel segmentation algorithm for high-throughput&#13;\\nanalysis of spectral domain-optical coherence&#13;\\ntomography imaging of teleost retina","year":2023,"lang":"en","type":"dissertation","venue":"Memorial University Research Repository (Memorial University)","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ocean Frontier Institute; Memorial University of Newfoundland","keywords":"Segmentation; Thresholding; Pixel; Image segmentation; Repeatability; Software; Optical coherence tomography; Process (computing)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008510022,0.0005866288,0.001106513,0.003338825,0.0007236147,0.0001054283,0.001527205,0.0006830656,0.00005322763],"category_scores_gemma":[0.0001382218,0.0007710568,0.0008270259,0.005945035,0.0008161094,0.0005671222,0.0002087663,0.001121543,0.00001651444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008031725,"about_ca_system_score_gemma":0.0006076623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003859504,"about_ca_topic_score_gemma":0.001696924,"domain_scores_codex":[0.9953445,0.0002913128,0.0007745574,0.001053223,0.001571515,0.0009649614],"domain_scores_gemma":[0.9951247,0.0009267716,0.0004462111,0.0008744349,0.002232419,0.000395475],"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":[0.007582633,0.002047715,0.002109684,0.003787981,0.006326866,0.0008625603,0.004560932,0.002459122,0.9197778,0.02415754,0.01007057,0.01625662],"study_design_scores_gemma":[0.02748841,0.003401131,0.02248584,0.002062552,0.007635427,0.00003864519,0.09035996,0.01024687,0.8143986,0.005100973,0.01085462,0.005927013],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9048098,0.0001100243,0.03193455,0.00007549387,0.0112394,0.004743011,0.001807455,0.0008127072,0.04446761],"genre_scores_gemma":[0.9006516,0.0005490184,0.06663638,0.000003904103,0.006622595,0.00003882639,0.005800987,0.0004712054,0.01922544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1053792,"threshold_uncertainty_score":0.999474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603736580367435,"score_gpt":0.2584497033669424,"score_spread":0.242412337563268,"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."}}