{"id":"W4379260521","doi":"10.1007/s10633-023-09932-z","title":"ISCEV guidelines for calibration and verification of stimuli and recording instruments (2023 update)","year":2023,"lang":"en","type":"article","venue":"Documenta Ophthalmologica","topic":"Ocular and Laser Science Research","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Guideline; Calibration; Medicine; Pathology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02120915,0.0009510316,0.001246783,0.003792084,0.001013589,0.00431238,0.004474706,0.006856482,0.03277426],"category_scores_gemma":[0.0621388,0.001007324,0.001690065,0.001886748,0.001354805,0.002329284,0.002717981,0.004456132,0.03460356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001942924,"about_ca_system_score_gemma":0.007818666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00999151,"about_ca_topic_score_gemma":0.0107055,"domain_scores_codex":[0.9687759,0.008456334,0.004873494,0.0008671482,0.01600566,0.001021447],"domain_scores_gemma":[0.9444324,0.01145039,0.002372481,0.003067178,0.03788756,0.0007899022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000205809,0.0001747607,0.001125142,0.001248209,0.00002718184,0.0003908028,0.0003576466,0.0004978814,0.002521131,0.006148622,0.7442283,0.2430746],"study_design_scores_gemma":[0.000062455,0.0001062612,0.002585139,0.002857854,0.00003040413,0.001521958,0.0001702051,0.0003077804,0.001820612,0.00306994,0.9874249,0.00004241049],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.009649486,0.09244907,0.2605624,0.06765775,0.0253621,0.01031273,0.04028944,0.01450569,0.4792113],"genre_scores_gemma":[0.05938663,0.08172017,0.3651347,0.07732041,0.007631403,0.02293233,0.09580953,0.006545117,0.2835197],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03277426,"threshold_uncertainty_score":0.112166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.167689097572409,"score_gpt":0.4401075120855596,"score_spread":0.2724184145131505,"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."}}