{"id":"W1903178851","doi":"10.46743/1540-580x/2006.1096","title":"Electronic Clinical Records for Physiotherapists","year":2006,"lang":"en","type":"article","venue":"Internet Journal of Allied Health Sciences and Practice","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Medical record; Documentation; Electronic records; Electronic data capture; Laptop; Personalization; Apprehension; Medicine; Computer science; Medical emergency; Psychology; World Wide Web; Clinical trial; Surgery","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02798602,0.0001654343,0.0006159655,0.0001575704,0.0006440564,0.00004362496,0.0003804241,0.0001673272,0.0000819905],"category_scores_gemma":[0.001591739,0.0001235205,0.0001223994,0.0002564075,0.0001838924,0.0005674699,0.00003891398,0.001271349,0.00002174879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004210556,"about_ca_system_score_gemma":0.005167409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003087008,"about_ca_topic_score_gemma":0.001826319,"domain_scores_codex":[0.9933406,0.002390386,0.00237434,0.0003202068,0.000444022,0.001130487],"domain_scores_gemma":[0.9858387,0.009730392,0.003441317,0.000145641,0.0005480184,0.0002960079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.007225331,0.001130522,0.04884285,0.003596341,0.0003352216,0.00001873151,0.00652828,0.00005134154,0.0001871288,0.2022,0.5855084,0.1443758],"study_design_scores_gemma":[0.001865475,0.006363762,0.00395992,0.0006098293,0.00001822789,0.0001969262,0.001384637,0.0006036256,0.00000379046,0.007834169,0.9770066,0.0001531077],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3713658,0.08520003,0.09012128,0.3733363,0.021189,0.007458825,0.00003335474,0.0001751245,0.05112028],"genre_scores_gemma":[0.9240837,0.01481351,0.02206554,0.02816029,0.006089994,0.00006104917,0.000003406807,0.00005264371,0.004669868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5527179,"threshold_uncertainty_score":0.9699451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1429923462124395,"score_gpt":0.5718424234906571,"score_spread":0.4288500772782176,"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."}}