{"id":"W4411226562","doi":"10.1111/den.15028","title":"Computer‐aided detection for esophageal achalasia (with video)","year":2025,"lang":"en","type":"article","venue":"Digestive Endoscopy","topic":"Gastroesophageal reflux and treatments","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Ipsen; Boston Scientific Corporation","keywords":"Medicine; Achalasia; Radiology; Artificial intelligence; Esophagus; General surgery; Internal medicine; Computer science","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":[0.003379645,0.0003708037,0.0003861772,0.0009667446,0.0001298436,0.0003340457,0.0003982327,0.0004502173,0.003460196],"category_scores_gemma":[0.01229297,0.0001464651,0.0003815741,0.0005016484,0.0001690417,0.0003223606,0.0003455224,0.0002506939,0.0006535365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003365165,"about_ca_system_score_gemma":0.0003002308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001435586,"about_ca_topic_score_gemma":0.002064144,"domain_scores_codex":[0.9979793,0.001083063,0.0001677755,0.0002815624,0.0004049065,0.00008345986],"domain_scores_gemma":[0.9891952,0.006667491,0.001961604,0.0004141532,0.001528531,0.0002329888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.009874227,0.0008879083,0.6028624,0.001588508,0.000732979,0.00042417,0.0002025679,0.00157217,0.01047269,0.0001248487,0.005174374,0.3660831],"study_design_scores_gemma":[0.000718212,0.007907004,0.9585829,0.0002142616,0.000500139,0.004643952,0.00009035323,0.007975063,0.01316731,0.00007767416,0.006059727,0.00006332885],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9710494,0.01112479,0.00983124,0.0003732483,0.0001356338,0.0006598658,0.001462178,0.0004828201,0.004880973],"genre_scores_gemma":[0.9850701,0.00144842,0.01099111,0.0001523781,0.00007896907,0.0001663778,0.0008345312,0.00001579854,0.001242455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003460196,"threshold_uncertainty_score":0.01787347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009953929860288112,"score_gpt":0.2891772208628836,"score_spread":0.2792232910025955,"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."}}