{"id":"W7103878905","doi":"10.2482/haigan.65.870","title":"How Can Surgeons Balance Clinical Practice and Research?","year":2025,"lang":"en","type":"article","venue":"Haigan","topic":"Surgical Simulation and Training","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Aging","funders":"","keywords":"Clinical Practice; Balance (ability); MEDLINE; Medical practice","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1014626,0.0008106248,0.001075184,0.003636344,0.006601966,0.02487709,0.002626912,0.01294379,0.01274097],"category_scores_gemma":[0.2866831,0.0007378394,0.0006510414,0.002937988,0.02085212,0.01790522,0.01404591,0.01004265,0.006001527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009772731,"about_ca_system_score_gemma":0.05669933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008943515,"about_ca_topic_score_gemma":0.02738475,"domain_scores_codex":[0.9267581,0.04644204,0.00310449,0.002856087,0.01527949,0.005559961],"domain_scores_gemma":[0.7122983,0.1482511,0.01585515,0.007887024,0.05312337,0.062585],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003354167,0.0004171298,0.01799359,0.001264665,0.0003454697,0.0002760455,0.007620326,0.0009015809,0.0004610032,0.1062407,0.4750661,0.389078],"study_design_scores_gemma":[0.0003691028,0.0003804016,0.01303787,0.005016142,0.0002316152,0.0005008229,0.04106969,0.000775857,0.000659808,0.3428923,0.5948092,0.0002571577],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.00271456,0.005060141,0.001001401,0.9749364,0.003654411,0.00001654314,0.00002787012,0.00004986177,0.01253889],"genre_scores_gemma":[0.3536031,0.02751386,0.01229518,0.5686359,0.0203932,0.0003658424,0.0001492984,0.0002829085,0.01676065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8985374,"threshold_uncertainty_score":0.5365918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.132934849422437,"score_gpt":0.4749103807267391,"score_spread":0.3419755313043021,"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."}}