{"id":"W3143869611","doi":"","title":"日本語版Toronto Extremity Salvage Score (TESS)-上肢の開発 : 言語的妥当性を担保した翻訳版の作成","year":2016,"lang":"ja","type":"article","venue":"Orthopaedic Surgery","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Surgery; Salvage surgery","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002869707,0.0009744374,0.001874859,0.0005412885,0.0003301272,0.00013142,0.0002939353,0.0005810604,0.004672742],"category_scores_gemma":[0.01179538,0.0007364218,0.002009225,0.000692541,0.0007914042,0.0004843015,0.0003028493,0.0006442886,0.003229933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006094476,"about_ca_system_score_gemma":0.00142013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004906488,"about_ca_topic_score_gemma":0.00008606679,"domain_scores_codex":[0.9931957,0.0005079376,0.001434686,0.001406678,0.001537011,0.001918035],"domain_scores_gemma":[0.9860431,0.009554699,0.0005328298,0.001987757,0.0004778956,0.001403702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002012538,0.0003126573,0.627624,0.0002800175,0.0002391514,0.001551274,0.0001637504,3.006211e-7,0.0006321318,0.000055528,0.1888628,0.1800772],"study_design_scores_gemma":[0.003265515,0.000100879,0.7236727,0.007089725,0.001309291,0.0004515519,0.0003117834,0.00001755947,0.0009601618,0.00009706915,0.2613211,0.001402624],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8316618,0.08569985,0.001813232,0.01198618,0.02754103,0.001226585,0.0008456149,0.001182498,0.03804328],"genre_scores_gemma":[0.9676191,0.00686795,0.0001067774,0.002220543,0.006634154,0.00007192304,0.0001431222,0.0002370312,0.01609937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1786745,"threshold_uncertainty_score":0.9995087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02607723221243653,"score_gpt":0.2562993028622473,"score_spread":0.2302220706498108,"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."}}