{"id":"W1803014567","doi":"","title":"Warning for surgeons: measure twice, cut once","year":2003,"lang":"en","type":"article","venue":"Europe PMC (PubMed Central)","topic":"Medical Malpractice and Liability Issues","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Neurosurgery; Medicine; Measure (data warehouse); General surgery; Surgery; Medical physics; Computer science; Data mining","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":[0.003473928,0.0005714581,0.0003671362,0.000592508,0.004334464,0.002173468,0.001052317,0.02218874,0.0237783],"category_scores_gemma":[0.03641988,0.000500349,0.0005688366,0.0003874394,0.002469282,0.003530135,0.001791997,0.01528758,0.0152663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00100412,"about_ca_system_score_gemma":0.003825437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006079274,"about_ca_topic_score_gemma":0.01075704,"domain_scores_codex":[0.9958293,0.0009426436,0.0004925107,0.000245053,0.002013368,0.0004771097],"domain_scores_gemma":[0.9862133,0.005520357,0.001465963,0.0007723675,0.003912353,0.002115747],"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":[0.00003252542,0.00003362793,0.001686446,0.00005224314,0.000008404929,0.0007055785,0.0007751964,0.00003107389,0.000893304,0.004604971,0.9706171,0.02055949],"study_design_scores_gemma":[0.00005678512,0.0001345097,0.006528717,0.0004702476,0.00002826163,0.006944038,0.003539515,0.0002998715,0.001293343,0.006961281,0.9736611,0.00008236327],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00579368,0.002409952,0.004394137,0.9095771,0.02212167,0.0000407039,0.00009457381,0.0006464827,0.05492185],"genre_scores_gemma":[0.04660222,0.001829534,0.00573733,0.8705673,0.007390039,0.00005951786,0.0001029458,0.0001689827,0.06754215],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0237783,"threshold_uncertainty_score":0.07954633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07509716112289684,"score_gpt":0.3581813384513618,"score_spread":0.283084177328465,"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."}}