{"id":"W7117241548","doi":"10.47391/jpma.20978","title":"Artificial intelligence for medical writing in doctors of Punjab; a cross-sectional study","year":2025,"lang":"en","type":"article","venue":"Journal of the Pakistan Medical Association","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sample (material); Quarter (Canadian coin); Medical writing; Medical science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch"],"domain":"methods","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch","scholarly_communication"],"domain":"reporting","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01321191,0.00008876471,0.0003478824,0.0002133623,0.0001171724,0.00004261257,0.0002616358,0.00030986,0.0002098864],"category_scores_gemma":[0.03033823,0.00006274169,0.0002122697,0.0005731322,0.00008387859,0.00008118158,0.00003958222,0.0007466513,0.000002932763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008593546,"about_ca_system_score_gemma":0.001811768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002184646,"about_ca_topic_score_gemma":0.0005304338,"domain_scores_codex":[0.9942915,0.0002317795,0.00325527,0.0001340334,0.001868974,0.0002184376],"domain_scores_gemma":[0.9948317,0.002980507,0.000861113,0.0001261559,0.001052407,0.0001480588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003260815,0.0008419085,0.9684034,0.00008595591,0.00007627345,0.000006511922,0.0009678963,0.00002528279,0.0000611296,0.001426376,0.0002638382,0.02751538],"study_design_scores_gemma":[0.000263551,0.0005717758,0.967365,0.0007976762,0.00009244735,0.00002641351,0.005855874,0.002410003,0.002815705,0.01933759,0.0003755846,0.00008834154],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816688,0.00008563046,0.004129212,0.01138667,0.002098863,0.0004485236,0.000002769563,0.000007830228,0.0001717065],"genre_scores_gemma":[0.9983781,0.00002652767,0.0001336407,0.0005086666,0.0007806739,0.00001313057,0.000001204582,0.000007927059,0.00015014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02742703,"threshold_uncertainty_score":0.9778296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09144913990637832,"score_gpt":0.4989946113269113,"score_spread":0.4075454714205329,"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."}}