{"id":"W1952783087","doi":"10.1002/alr.21496","title":"Identification of chronic rhinosinusitis phenotypes using cluster analysis","year":2015,"lang":"en","type":"article","venue":"International Forum of Allergy & Rhinology","topic":"Sinusitis and nasal conditions","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute on Deafness and Other Communication Disorders; National Institutes of Health","keywords":"Medicine; Chronic rhinosinusitis; Cluster analysis; Hierarchical clustering; Fibromyalgia; Internal medicine; Artificial intelligence; 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":[0.003130717,0.0007650459,0.0008397943,0.004454347,0.0007494022,0.001216843,0.0007131022,0.0003474558,0.001194361],"category_scores_gemma":[0.007128597,0.0001912724,0.0009575466,0.00210487,0.0005047623,0.0004264704,0.001016824,0.0006059316,0.0003363095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000898803,"about_ca_system_score_gemma":0.00136057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005783986,"about_ca_topic_score_gemma":0.004548076,"domain_scores_codex":[0.9982456,0.0006419855,0.0001918547,0.0003941238,0.000394572,0.0001319324],"domain_scores_gemma":[0.9964127,0.001166967,0.0006795601,0.0003900547,0.001129169,0.0002216386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001477815,0.0005019733,0.7897282,0.0003510877,0.0007929698,0.0003813973,0.001518188,0.02105091,0.01118885,0.002019029,0.004717983,0.1662716],"study_design_scores_gemma":[0.0002174355,0.0005558238,0.7607533,0.0001539169,0.0002590534,0.000953602,0.001227343,0.2209069,0.003510593,0.007256413,0.004081147,0.0001243173],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8756301,0.0006145578,0.1170972,0.0004276563,0.00006888541,0.001287997,0.001742996,0.000602047,0.002528582],"genre_scores_gemma":[0.9089088,0.0001293131,0.0875084,0.00003717996,0.00003879234,0.0005169945,0.002491763,0.00005158271,0.0003172616],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005783986,"threshold_uncertainty_score":0.01655704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02684821587548988,"score_gpt":0.3126348207950478,"score_spread":0.285786604919558,"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."}}