{"id":"W2147581528","doi":"10.2460/javma.2004.225.222","title":"Use of the Roter interaction analysis system to analyze veterinarian-client-patient communication in companion animal practice","year":2004,"lang":"en","type":"article","venue":"Journal of the American Veterinary Medical Association","topic":"Veterinary Practice and Education Studies","field":"Health Professions","cited_by":104,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"OVC Pet Trust","keywords":"Companion animal; General partnership; Medicine; Conversation; Family medicine; Sample (material); Population; Descriptive statistics; Psychology; Medical education; Nursing; Veterinary medicine; Communication; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004947044,0.0002784084,0.0002876955,0.001974117,0.0003226567,0.0006473483,0.0003794441,0.0002508766,0.002735044],"category_scores_gemma":[0.01989975,0.0001866175,0.000268185,0.001262912,0.0002916455,0.0005767285,0.0005876808,0.0003071715,0.0005515027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006282713,"about_ca_system_score_gemma":0.00105978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003154515,"about_ca_topic_score_gemma":0.005154456,"domain_scores_codex":[0.9952227,0.00344349,0.000433491,0.0002411736,0.0004976222,0.0001615307],"domain_scores_gemma":[0.9834158,0.009627241,0.003821606,0.0005733036,0.002214673,0.0003473033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001557143,0.0005055122,0.7222649,0.000593168,0.0001026298,0.0004194664,0.01638184,0.0006980014,0.005838267,0.0002270489,0.002071611,0.2493405],"study_design_scores_gemma":[0.0001402356,0.002635399,0.9714301,0.0001425758,0.00008250034,0.0009895426,0.01040441,0.007182952,0.002598047,0.000145845,0.004183934,0.0000644597],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9892126,0.0002471865,0.00674954,0.00008943124,0.000008787323,0.0007035499,0.0006325181,0.0002571346,0.002099238],"genre_scores_gemma":[0.9732684,0.0002141591,0.02359562,0.00004462598,0.00001728827,0.001350248,0.0006415198,0.00002216777,0.0008460422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004947044,"threshold_uncertainty_score":0.0261628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1503596570049876,"score_gpt":0.4691155749566456,"score_spread":0.318755917951658,"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."}}