{"id":"W4396504849","doi":"10.1164/ajrccm-conference.2024.209.1_meetingabstracts.a1756","title":"Edmonton Dyspnea Inventory (EDI) Is a Reliable Tool for Detecting Dyspnea in Interstitial Lung Diseases (ILDs)","year":2024,"lang":"en","type":"article","venue":"","topic":"Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Lung; Medicine; Computer science; Pathology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002149764,0.001129506,0.001103159,0.002379778,0.0004825688,0.0008711697,0.0006346239,0.0007613385,0.002838239],"category_scores_gemma":[0.00406105,0.000237032,0.001074752,0.0007742852,0.0002799963,0.0007662562,0.0011127,0.0007383339,0.0006941338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000486014,"about_ca_system_score_gemma":0.0007259148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003105172,"about_ca_topic_score_gemma":0.00927655,"domain_scores_codex":[0.9985861,0.0003225984,0.0002216142,0.0001693902,0.0005488861,0.0001513803],"domain_scores_gemma":[0.9979926,0.0005349605,0.0006446815,0.00006047637,0.000523899,0.0002433245],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003564393,0.0005951324,0.9462991,0.0003453856,0.0004991757,0.0003620133,0.0001871456,0.0005111421,0.001637045,0.0001912568,0.007361031,0.04165513],"study_design_scores_gemma":[0.00003310704,0.0003345516,0.9957224,0.00009863212,0.00009648607,0.0004123949,0.00008148872,0.0006633222,0.000380737,0.00009817099,0.002053997,0.00002469178],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9075878,0.01458533,0.006527546,0.001373742,0.0007131163,0.001671926,0.0166584,0.0004788889,0.0504033],"genre_scores_gemma":[0.9705859,0.003375408,0.01035859,0.0008511544,0.0002695914,0.000701513,0.007227664,0.00003157687,0.006598608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003105172,"threshold_uncertainty_score":0.01136917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01069584723405246,"score_gpt":0.2800302676121747,"score_spread":0.2693344203781222,"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."}}