{"id":"W2021874121","doi":"10.1111/aos.12479","title":"Grader learning effect and reproducibility of Doppler Spectral‐Domain Optical Coherence Tomography derived retinal blood flow measurements","year":2014,"lang":"en","type":"article","venue":"Acta Ophthalmologica","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Repeatability; Reproducibility; Optical coherence tomography; Medicine; Retinal; Ophthalmology; Session (web analytics); Grading (engineering); Nuclear medicine; Biomedical engineering; Computer science; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004113311,0.0005102893,0.0006516385,0.0008026276,0.0003152628,0.0007416486,0.0006151772,0.000644804,0.001717526],"category_scores_gemma":[0.0238336,0.0002565631,0.0005385389,0.0002444101,0.0004861689,0.0006617684,0.00114008,0.000464497,0.0005596392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002708629,"about_ca_system_score_gemma":0.0001236607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007926283,"about_ca_topic_score_gemma":0.001237456,"domain_scores_codex":[0.9951945,0.001172026,0.0005724422,0.001302267,0.001484733,0.0002740651],"domain_scores_gemma":[0.9690356,0.01406639,0.006313956,0.005454163,0.004140798,0.0009890988],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003137897,0.0007836096,0.9397683,0.0001394073,0.0007054777,0.0003636846,0.00149286,0.0005895268,0.01486027,0.0001039136,0.0005636167,0.03749152],"study_design_scores_gemma":[0.00002663555,0.001981295,0.992938,0.00001199556,0.00008320012,0.0004097107,0.0001780376,0.001023833,0.002884233,0.00005904742,0.0003834245,0.0000206333],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976065,0.0002693845,0.001201861,0.00002073464,0.00003523381,0.00003383884,0.0001093533,0.00004250985,0.0006804878],"genre_scores_gemma":[0.9987515,0.00003710505,0.000496434,0.0000203757,0.00001515695,0.00001937934,0.0001537092,0.00002031879,0.0004859763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9958867,"threshold_uncertainty_score":0.02175355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02379739449931974,"score_gpt":0.2496406513304988,"score_spread":0.225843256831179,"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."}}