{"id":"W7162021944","doi":"10.82308/1877","title":"Determining agreement between physician claims data and medical chart documentation for polypectomy","year":2010,"lang":"en","type":"dissertation","venue":"","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Documentation; Concordance; Medical record; Medical audit; Polypectomy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.06834895,0.0003495327,0.0008228355,0.006022003,0.0006070553,0.002680456,0.001451305,0.0009478096,0.00179554],"category_scores_gemma":[0.2592826,0.0004272943,0.001010423,0.005331538,0.0007471855,0.001518449,0.002077082,0.0007632392,0.0005046807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002430356,"about_ca_system_score_gemma":0.002909419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03307417,"about_ca_topic_score_gemma":0.0281698,"domain_scores_codex":[0.9415163,0.03122815,0.009278011,0.004141042,0.01251566,0.001320798],"domain_scores_gemma":[0.6657997,0.2130792,0.06396373,0.01362676,0.04194704,0.001583539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002747106,0.00003092127,0.9893015,0.0001851351,0.0002260824,0.00002047255,0.001031893,0.0002592344,0.0001230103,0.0001623807,0.0005539429,0.007830756],"study_design_scores_gemma":[0.00002927203,0.0001585385,0.9913563,0.000317569,0.0001547272,0.0001031828,0.001009467,0.003307686,0.0006105119,0.0002514908,0.002671569,0.00002968905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9661818,0.00256759,0.01044955,0.0009919571,0.0001315912,0.0005930937,0.01191439,0.0001078067,0.007062102],"genre_scores_gemma":[0.990271,0.0003220771,0.004769972,0.0001801912,0.00004523532,0.0002778995,0.0035703,0.00001587452,0.0005475318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06834895,"threshold_uncertainty_score":0.3614681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03540765024848907,"score_gpt":0.3705806370885045,"score_spread":0.3351729868400154,"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."}}