{"id":"W4414744464","doi":"10.2196/79280","title":"Quantitative Assessment of Strabismus Using Cloud AI Computing: Validation Study","year":2025,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Ophthalmology and Eye Disorders","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quantitative assessment; Cloud computing; Telehealth; Strabismus; Cover (algebra); Cloud cover","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00175651,0.000100759,0.0002992113,0.0005029158,0.0002347819,0.0000182468,0.0001182724,0.00007901758,0.00006929335],"category_scores_gemma":[0.0001275239,0.000086354,0.00006116278,0.0008736894,0.0002484292,0.0001586054,0.0001264077,0.0006022006,0.00001065828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001508905,"about_ca_system_score_gemma":0.0004089776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008382368,"about_ca_topic_score_gemma":0.000002385005,"domain_scores_codex":[0.9980459,0.0005990282,0.0003517962,0.0001850306,0.0005199182,0.0002982802],"domain_scores_gemma":[0.9985508,0.0003719025,0.00008427279,0.0002221511,0.0007199459,0.0000509253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001432477,0.009270804,0.8980301,0.001416553,0.001138629,0.00007913459,0.03752817,0.001119991,0.006461641,0.03771966,0.00260907,0.003193751],"study_design_scores_gemma":[0.003174028,0.005048058,0.8863683,0.0003424088,0.00005464591,0.00001209408,0.06169522,0.03863702,0.002412006,0.002074065,0.000060832,0.0001213253],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831368,0.00003392862,0.003830512,0.000450523,0.0001526256,0.001166801,0.00000558752,0.00001651926,0.01120668],"genre_scores_gemma":[0.9991642,0.00000317151,0.0005903102,0.00003058449,0.00001536532,0.00002460955,0.00001962489,0.000007062671,0.0001450885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03751703,"threshold_uncertainty_score":0.3521414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.155383136447484,"score_gpt":0.5744247316143595,"score_spread":0.4190415951668754,"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."}}