{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001775926,0.0004830286,0.0002853642,0.001011978,0.0003387113,0.000522975,0.0005021079,0.0003757413,0.001350479],"category_scores_gemma":[0.007485181,0.0001244671,0.0004429977,0.0006881721,0.0005056036,0.000427542,0.00068251,0.0002793795,0.0003833112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005367668,"about_ca_system_score_gemma":0.0004998339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004146373,"about_ca_topic_score_gemma":0.003620782,"domain_scores_codex":[0.9984106,0.0005049934,0.0001845557,0.000231896,0.0005671234,0.0001007555],"domain_scores_gemma":[0.9935837,0.00191166,0.0009007618,0.0007651325,0.0025391,0.0002995976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003232463,0.004118736,0.7585689,0.000944962,0.0005577379,0.0005216663,0.001947733,0.01177996,0.04122267,0.0008397395,0.00210901,0.1741565],"study_design_scores_gemma":[0.0002747737,0.009114325,0.8875252,0.0002092974,0.000291758,0.001388606,0.001666126,0.07611448,0.01954787,0.000458836,0.003340987,0.00006770711],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928888,0.0001520842,0.005326847,0.00001753776,0.00001134989,0.0003670892,0.0003371913,0.00006336484,0.0008356165],"genre_scores_gemma":[0.9939475,0.00009299325,0.004980873,0.00002152068,0.000006992776,0.000173479,0.0005438832,0.0000109065,0.0002217711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004146373,"threshold_uncertainty_score":0.009392083,"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."}}