{"id":"W4404107901","doi":"10.22374/jclrs.v8i1.63","title":"EVALUATING THE LEARNING CURVE OF A NOVICE OPTOMETRY STUDENT IN SCLERAL LENS FITTING: A PROSPECTIVE QUANTITATIVE STUDY USING DELIBERATE PRACTICE AND CUMULATIVE SUMMATION (LC-CUSUM)","year":2024,"lang":"en","type":"article","venue":"Journal of Contact lens Research and Science","topic":"Ophthalmology and Visual Health Research","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CUSUM; Learning curve; Optometry; Scleral lens; Ophthalmology; Lens (geology); Medicine; Psychology; Computer science; Mathematics; Statistics; Optics; Contact lens; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.008344127,0.0004226104,0.0006070501,0.001795231,0.001026591,0.001866438,0.000775261,0.001062426,0.001962775],"category_scores_gemma":[0.02308137,0.0005979905,0.000749203,0.000629075,0.001385448,0.001274161,0.001620053,0.001428895,0.0007384148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009039217,"about_ca_system_score_gemma":0.001364571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007695499,"about_ca_topic_score_gemma":0.001227445,"domain_scores_codex":[0.9947652,0.001778963,0.0005012084,0.0006031495,0.001690081,0.0006613605],"domain_scores_gemma":[0.9707704,0.009707893,0.006810527,0.001199661,0.007376633,0.004134772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00059053,0.009653289,0.9033301,0.0003364684,0.00008415979,0.0006357617,0.04587042,0.000591856,0.004143027,0.0001537399,0.0004426195,0.03416806],"study_design_scores_gemma":[0.00006943897,0.01940259,0.9249278,0.000161505,0.00005252407,0.001563152,0.04425834,0.002366432,0.003825811,0.0002216806,0.002982678,0.0001680611],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990944,0.00003630602,0.0003782294,0.00002619625,0.000002944945,0.0001027218,0.00002277081,0.000005240468,0.0003311808],"genre_scores_gemma":[0.9978872,0.00007908931,0.001212498,0.0000672532,0.00000618052,0.0001406661,0.00005716066,0.000007171232,0.0005427914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008344127,"threshold_uncertainty_score":0.04412848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5057251025350258,"score_gpt":0.6784572017426703,"score_spread":0.1727320992076445,"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."}}