{"id":"W4386592608","doi":"10.1002/ase.2336","title":"Evaluating AI‐powered text‐to‐image generators for anatomical illustration: A comparative study","year":2023,"lang":"en","type":"article","venue":"Anatomical Sciences Education","topic":"Anatomy and Medical Technology","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Trunk; Depiction; Anatomy; Fibrous joint; Perspective (graphical); Medicine; Computer science; Artificial intelligence; Biology; Visual arts; Art","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":[],"consensus_categories":[],"category_scores_codex":[0.01231372,0.0009455005,0.000752013,0.003839836,0.0007484544,0.002140382,0.001529856,0.001539456,0.0101558],"category_scores_gemma":[0.07239746,0.0003767352,0.001239024,0.00135946,0.001137322,0.00229883,0.00159201,0.0006505675,0.001750564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001060829,"about_ca_system_score_gemma":0.0005316536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007252051,"about_ca_topic_score_gemma":0.001047669,"domain_scores_codex":[0.9938451,0.003056993,0.0008212129,0.0004573548,0.001617598,0.0002018263],"domain_scores_gemma":[0.9088383,0.07166077,0.00277208,0.004725037,0.01055905,0.001444901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01873414,0.01936038,0.07878333,0.00715206,0.001015036,0.006287969,0.03311928,0.01747578,0.0695961,0.00638844,0.01100794,0.7310796],"study_design_scores_gemma":[0.006845525,0.1311691,0.4328828,0.002969657,0.003924219,0.02829706,0.03276793,0.1288196,0.1130662,0.01213951,0.1057926,0.001325849],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9711018,0.001283332,0.012828,0.0001821092,0.0001270848,0.001867582,0.0004420651,0.0003131533,0.01185483],"genre_scores_gemma":[0.9559634,0.001193385,0.03748618,0.0002042196,0.0001063205,0.0008269122,0.0006327796,0.0002626985,0.003324238],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01231372,"threshold_uncertainty_score":0.06512195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07740633814476437,"score_gpt":0.4253460389688154,"score_spread":0.347939700824051,"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."}}